Information

Does white noise impair studying, reading, recall/memory or learning?

Does white noise impair studying, reading, recall/memory or learning?



We are searching data for your request:

Forums and discussions:
Manuals and reference books:
Data from registers:
Wait the end of the search in all databases.
Upon completion, a link will appear to access the found materials.

I recently have been trying to look into whether or not white noise works as a means to block out external sounds so I can concentrate. However, I want to know whether it actually impairs studying and reading. I do not care if it has no benefit, as long as it has no negative effects.

I am trying to block out the sounds of my brother through the walls when he is playing his xbox. As I am hyper-sensitive to noise and any abrupt noises what so ever throw me out of my concentration.


There are recent studies that suggest that unstructured background noise, including white noise, may actually improve studying and recall. The benefits are unclear and likely person-dependent, but there is at least no obvious bad effect.

Bottom line: sounds like a safe strategy for you to try.


Reading People: Behavioral Anomalies and Investigative Interviewing

While interviewing a crime suspect a police officer asks what happened. For an instant the interviewee’s eyes get wide so that the white above the irises is visible. The suspect’s story begins with details about memories from before the incident, including things the alleged offender did and did not do. The suspected criminal describes the event while wringing the hands and looking away, up and to the left, not making direct eye contact. The interviewee’s speech becomes slower and references to other people change with the use of pronouns. The suspect, whose left eyebrow is twitching, does not speak about the incident itself and finishes the story with “and that's about it.” 

The description above makes much of this individual’s story suspicious from a credibility assessment standpoint. However, when conducting interviews, investigators must ask themselves some important questions based on their observation of behavioral anomalies.                              

  • What cues contribute to the determination, and why?
  • Which behaviors are meaningful signs, and which are not?
  • Which actions are true signals of something important, and which are just noise?
  • Which signs provide guidelines for further probing and questioning?
  • What insights can be gained from the observed indicators, and why?

Many law enforcement professionals understand and appreciate the importance of behavioral anomalies. These verbal and nonverbal signs of cognitions and emotions provide additional clues to what an individual is thinking and feeling beyond the content of the words being spoken. In the context of investigative interviewing, these behavioral anomalies are called indicators.

These anomalies provide important cues and valuable insight into the personality, motivation, and intention of suspects. They can be signs of hostile intent, suspicious behavior, veracity or lying, or topics and concerns that are important to the interviewee. These crucial bits of knowledge give investigators information superiority that can guide them through the process and help them complete interviews. Individuals typically do not know that they are revealing these indicators.

Dr. Matsumoto is a professor of psychology at San Francisco State University and director of a private training and consulting firm in California. 

Ms. Skinner is a retired FBI Supervisory Special Agent and former instructor at the FBI Academy in Quantico, Virginia.

Dr. Hwang is a research scientist and vice president of a private training and consulting firm in California.

When reading people, one important distinction interviewers must make is the difference between validated and nonvalidated indicators. Those that are validated have scientific and field evidence documenting the association between the behavior and specific cognitions or emotions. These anomalies are laboratory tested under strict scientific conditions and vetted in the field by practitioners. Nonvalidated indicators lack such data—either in scientific evidence, field operations, or both. 1

Validation provides evidence for accuracy and consistency across various people in different contexts. Noticing that a suspect’s hands were held in a certain way when describing an incident that later turned out to be a lie is not evidence that the behavior is indicative of lying for other people in varying situations. Observation alone is not sufficient to label a certain behavior as a validated indicator because it has not withstood the scrutiny of rigorous testing in the laboratory and the field. Such testing would require establishing the conditions in which the indicator may or may not occur with multiple people. If the behavior ensued that would be evidence for its validation, and if it did not that would be verification for its nonvalidation.

There are validated and nonvalidated indicators imbedded in the example at the beginning of this article. The flash of the eyes so that the white above the iris is seen is a validated indicator of concealed fear, and the suspect’s comments about behavior that did not occur are indicative of a potential lie. Looking up to the left and twitching of the left eyebrow are not validated indicators of lying, even though many people believe they are.

Programs that teach nonvalidated indicators produce negative results in people’s ability to detect lies from truths. 2 For example, a common belief is that a lack of eye contact is an indicator of lying however, numerous studies have tested this and most do not support it. Therefore, this belief is more myth than reality. 3 A recent study showed that liars know this too and compensate for it by looking the interviewer straight in the eye more than truth tellers. 4

There are two categories of validated behavioral indicators that are relevant to interrogations. One involves linguistic markers used in words when individuals provide statements or answer questions. This category is entirely verbal—based on principles of human memory and recall—and suggests that lies are different from truths in their demands upon memory, which is reflected by changes in grammar and language. Research has indicated that lies comprise fewer words and more omissions of information are less plausible, structured, and logical are more discrepant and ambivalent contain repeated details lack contextual imbedding and include more descriptions of what did not occur. 5 These findings lead to specific linguistic and grammatical indicators of veracity and lying—such as the use of negation, extraneous information, and different types of adverbs—that may be identified in statements and interviews.

The second category includes nonverbal behaviors (NVB). Research has shown that various emotions and cognitions are communicated through facial expression, voice tone, gesture, body movement, and posture. 6 In the investigative context, NVB indicators occur because conflicting thoughts and feelings transpire when people lie and are under stress but attempt to hide their feelings and expressions. These anomalies often leak out nonverbally. Research has established that NVB indicators of lying include changes in the use of speech illustrators and symbolic gestures subtle and microfacial manifestations of facial expressions variations in blinking, pauses, and speech rates and outward attempts to regulate emotions. 7

It is possible to train individuals to identify verbal and nonverbal indicators of truthfulness and lying. Verbal indicators are acknowledged through analysis of specific linguistic markers and words using Statement Analysis (SA)—also known as Statement Validity Analysis, Criteria-Based Content Analysis, Reality Monitoring, and Scientific Content Analysis. 8 Nonverbal indicators are identified as subtle or microfacial expressions of emotion, gestures, vocal changes, and body language. 9

Statement and nonverbal analysis are not new to law enforcement as the techniques have been taught to investigators for years. However, in real-life, indicators of veracity and lying occur simultaneously, and awareness of both increases an investigator’s ability to identify meaningful content areas of an interview detect clues to deceit and provide additional insight into the thoughts, feelings, personality, and motivation of the interviewee. People sometimes produce verbal indicators with no NVB and NVB indicators without talking. Investigators who pay attention solely to one or the other may miss valuable information.

The importance of considering verbal and nonverbal indicators concurrently was highlighted in a recent study—published in the FBI Law Enforcement Bulletin—that examined the combined contributions to the prediction of deception or truthfulness. 10 The study showed that members of ideologically-motivated groups committed one of two types of lies. In one, participants were placed in a situation where they could commit a crime—steal $50 in cash from a briefcase—and later were interviewed about whether they carried out the crime or not (the crime scenario). In another setting, individuals chose to lie or tell the truth about their beliefs concerning their political cause (the opinion scenario). Regardless of the circumstances, there were stakes involved—if they were judged as lying, they would lose their participation fee and face one hour of white noise blasts while sitting on a cold, steel chair in a small, cramped room.

Videos of 20 individuals󈟚 each from the crime and opinion scenarios, half truth tellers and half liars—were analyzed. Analyses of their words and NVB together led to a 90 percent accuracy rate for classifying the individuals as lying or telling the truth. Compared to the average accuracy rate of 53 percent—no better than chance—by observers in previous studies, the findings indicated that behavioral anomalies in verbal statements and NVB collectively provided a better source for determining veracity and deceit than basic observation. 11

Investigators gained valuable information within 40 seconds of an interview with a 42-year-old female suspect who allegedly assaulted a minor. After officers Mirandized and obtained background information from the suspected perpetrator the discussion ensued—nonverbal behaviors are italicized.

The investigator asked, “Mary, do you know the reason why you’re here today?”

Mary replied, “I have no idea.” She smiled, leaned forward, and showed concern on her face. Her voice sounded vulnerable.

The investigator said, “Okay…the reason why you’re here today is that an allegation has been made on you…”

Mary responded, “Okay.” She spoke softly while nodding her head.

The investigator continued, “…that you assaulted Joe.”

Mary’s brows went up and her eyes opened wide so that the whites above the eyes could be seen. Her jaw dropped and her mouth opened.

The investigator asked, “Do you know who Joe is?”

Mary replied, “I have no idea.” She shook her head quickly and gave a brief microfacial expression of disgust.

The investigator said, “Joe lives down the street from you.”

Mary (displaying another microfacial expression of disgust) asked, “What?” She spoke incredulously, leaned forward, and smiled.

The investigator inquired, “An allegation came out that you assaulted him. He’s 13 years old. I’m just going to point blank ask you, did you have anything to do with it?”

Mary (smiling) responded, “No. He was definitely hitting on…. It was one night when they spent the night over (smiling) and he was acting kind of strange that night and nothing happened.”

At the beginning when Mary was asked if she knew why she was in the interview, Mary smiled, leaned forward, looked concerned, and said in a vulnerable voice, “I have no idea.” Her coy, almost flirtatious demeanor suggested that this may be a major characteristic of her personality. Mary said “Okay” when the investigator stated that an allegation had been made about her. This implied that she knew what the investigator was talking about and could speak to her participation in the incident. It also could have indicated that Mary merely was tracking the conversation by acknowledging what was being said—known as back-channel communication. Knowing her baseline would help the investigator make this distinction.

Mary’s eyes widening for an instant indicated fear, suggesting that she was afraid of something but trying to control her outward display—as opposed to someone who was innocent but afraid of being misbelieved, in which case the fear would not be displayed as a microexpression. When Mary said that she had no idea who Joe was but exhibited two microexpressions of disgust, this suggested that she knew exactly who Joe was—part of her brain was processing information that was incongruent with what she was saying. She then revealed that she did know Joe, despite having just denied it, by stating, “He was definitely hitting on…” before she stopped herself. Mary saying “It was one night…” indicated that this was an incident she knew about. When Mary tried to stop the conversation by saying that “nothing happened” this signified that something actually had happened, but she was omitting the facts.

This example demonstrates how verbal and nonverbal indicators of veracity and deceit occur simultaneously during communication. They are woven into the ongoing interaction and convey a wealth of information above and beyond the surface meaning of the words. It would benefit officers to identify these indicators when conducting interviews. Their detection provides valuable assistance for guiding the investigator to meaningful content areas, helping build cases strategically and tactically, developing themes for use in interrogations, and arriving at ground truth quickly and accurately.

The techniques for both statement and NVB analysis typically have been taught separately to law enforcement officers, providing them with increased skill in one particular technique but resulting in their missing much of the useful information that interviewees impart. A few years ago the FBI National Academy (NA) began offering a course on investigative interviewing that united the techniques of statement and NVB analysis. Merging these techniques into a single application was a risk however, it was possible that training in both could produce an information overload such that their practical application would have been unsuccessful. Trainees learning both techniques independently often reported that they were overwhelmed by the amount of detail to which they had to attend. Fortunately, combining the techniques produced positive results and the benefit of more real-life circumstances.

Mid-to-upper-level career law enforcement officers concurrently enrolled in two courses—one was a traditional course on statement analysis (trainees had to learn the basics of SA) and the other was a combined SA and NVB analysis course. Both courses covered validated indicators of truthfulness and lying culled from research and included lectures, discussions, video reviews, group projects, and individual practicum. After learning the basic principles of both statement and NVB analysis, trainees practiced on realistic source materials—actual statements and videos of suspects, witnesses, and informants telling truths and lies—to hone their skills. The combined course also required trainees to learn how to recognize microfacial expressions of emotion.

By the end of the courses, trainees had improved their capacity to recognize verbal and nonverbal indicators of veracity and deceit and to incorporate those skills into their interview strategies. Pre- and post-test data on their ability to detect truths from a standardized set of videos were obtained in three sessions. At the beginning of the courses, attendees viewed a set of 10 videos prior to any training in SA or NVB analysis. Participants watched a different set of 10 videos at the end of the courses. The videos were switched across both courses so that any findings were not specific to one set. A sizable increase in accuracy rates—between 10 and 25 percent—in the trainees’ ability to detect lies from truths resulted (Figure 1). These improvement rates were remarkable since the test videos lasted only 60 to 90 seconds. If the trainees had been able to question the interviewees in person, in a longer interview, with other typically available sources of evidence—forensics, witness statements, and physical evidence—the increase could have led to substantial differences in the efficacy by which investigators obtain ground truth and close cases.

Figure 1 - Accuracy Rates Before and After Training, Separately for All Videos and Crime Videos Only

Although trainees initially reported being overwhelmed by the details, they expressed greater comfort with the techniques by the end of the sessions. Many students reported that after learning and applying both statement and nonverbal behavior analysis they recognized so many indicators that too many potential clues providing insight into interviewees’ minds became apparent. They had to prioritize and determine which ones to act on, thereby producing the collateral benefit of improving their thinking about interrogation strategies and tactics.

Behavioral anomalies—the verbal and nonverbal indicators of veracity and deceit—occur simultaneously in real-life. Recognizing these indicators helps investigators detect lies and gain insight into the personality, motivation, and internal conflicts of interviewees and identify content areas necessitating further exploration and discovery. Law enforcement officers must imbed these techniques within their strategic interview methodology.

Behavioral anomalies are signs investigators can use to determine truth however, they should not be interpreted strictly given that research has not identified any behavior or behavior combinations that are unique to lying. 12 They are highly dependent upon the interviewer’s skills and should be used strictly as a means to an end.

Using behavioral anomalies in investigative interviewing will not solve every case. Interviews should be augmented by witness statements, forensics, and other evidence. Investigators must prepare and plan for interviews, develop questions, and guide discussions as they recognize indicators. Those who have lie detection training must be cautious of post-training biases. 13 However, identifying valid indicators—both verbal and nonverbal—remains a useful tool for any law enforcement investigator.

Additional information may be obtained from the authors at [email protected], [email protected], or lisaglennskinne[email protected] 

1  There are different types of nonvalidated indicators. For example, potential indicators that have never been tested scientifically should be considered unvalidated indicators. Potential indicators that have been tested scientifically but did not produce reliable findings would be considered invalidated indicators. For the purposes of this article, both are called nonvalidated indicators.


One explanation is that different people need different amounts of noise for optimal arousal and optimal performance.

Stochastic resonance is a natural phenomenon, whereby a certain amount of noise improves the ability to detect a signal. By introducing noise, signals that are below the perception threshold are boosted enough so that they can be perceived. For example, adding a certain amount of auditory noise allows you to hear sounds that were previously undetectable by your ears.

If you add too much noise though, you decrease the signal-to-noise ratio the louder the noise the more you drown out the sound in the end, it becomes indiscernible in the noise. This is how sound masking works. So there can be too little and too much noise!

Stochastic resonance can be observed in many different domains. This also includes our brain’s neural systems:

The researchers in the above-mentioned studies suggest that inattentive people might have too little noise in their neural systems. By adding white noise, their brain is pushed towards optimal arousal and better cognitive functioning. At the same time, people who are already optimally aroused are getting overstimulated by the white noise.

The amount of noise needed for optimal arousal varies from person to person.

In a very recent study, exposed to white noise played through headphones at 80 dB(A), children suffering from ADHD showed a much improved visual working memory and verbal recall ability compared to a quiet control condition. Their performance approached that of typically developed children whose performance declined slightly (but not significantly) under white noise. In that particular experiment, white noise was more effective than ADHD medication!

I would argue that the amount of noise needed for optimal arousal varies even in a single person, for example, depending on the time of the day, nutrition, and the amount of sleep they have had.

Last night, I only slept 5 hours, and today – white noise helps me to stay awake!


Discussion

Previous work on noise benefits in neural processing and cognition has highlighted different, albeit not mutually exclusive, underlying mechanisms. Closely related to the physical concept of stochastic resonance (Gammaitoni et al., 1998), it has been stated that an optimal level of noise added to a subthreshold sensory signal can cause threshold crossing and thus enhance sensitivity for weak signals (Douglass et al., 1993 Collins et al., 1995 Wiesenfeld and Moss, 1995 Zeng et al., 2000 Moss et al., 2004). Moreover, noise has been linked to intra- and interregional neural synchronization (Moss et al., 2004 Ward et al., 2010). And finally, based on psychopathology research (Sikström and Srlund, 2007), a link has been suggested between noise benefits and dopaminergic neuromodulation. By altering the ratio of tonic and phasic activity in the dopaminergic midbrain (i.e., SN/VTA) and its connectivity with higher cortical areas (i.e., superior temporal sulcus) (Rausch et al., 2013), externally applied noise might act on salience assessment (Redgrave et al., 1999 Horvitz, 2000), resource allocation (Boehler et al., 2011 Krebs et al., 2011), and cortical signal-to-noise ratio (Mattay et al., 1996, 2003 Li et al., 2001 Mattay et al., 2002 Winterer and Weinberger, 2004 Kroener et al., 2009). Other neurochemical systems such as GABA or norepinephrine, however, might also be involved (Coull et al., 2004 Samoudi et al., 2012).

The current study investigated the effects of acoustic white noise on attentional and mnemonic processes that strongly depend on dopaminergic signaling. Performance in a change detection task, a monetary incentive encoding task, and the Posner task was compared for concurrently presented white noise, a pure tone, and silence. Sound levels of 70dB were chosen based on previous studies showing an effectiveness of similar noise levels in improving mnemonic functions (Usher and Feingold, 2000 Rausch et al., 2013), although it should be noted, that some studies used slightly higher noise levels at around 75� dB (e.g., Carlson et al., 1997 Srlund et al., 2010). Since, in the current study, pleasantness of pure tone and white noise were both rated slightly aversive on average (and strongly aversive by some subjects) already at 70 dB, we, however, suggest being careful when applying higher sound levels for an extended time period without individual adjustment. We hypothesized that white noise but not a pure tone would increase performance and that beneficial effects would correlate with personality dimensions known to be associated with interindividual differences in dopaminergic system parameters. These predictions could not be fully confirmed, leaving the modulatory influence of noise on higher cognitive functions a subject for further investigations.

Experiments 1𠄳

Contrary to our expectation, working memory performance was impaired when white noise was presented in the delay period of a delay-match-to-sample task. This effect was selective for white noise and not a general effect of auditory stimulation, since the pure tone did not affect performance. This finding is in contrast to previously shown beneficial effects of white noise on working memory performance in monkeys (Carlson et al., 1997), but resembles deteriorating effects of white noise on memory for verbal sentences in healthy controls (Srlund et al., 2007).

The systematic variation of sound presentation in Experiments 1𠄳 makes it possible to localize a time period and the associated cognitive function sensitive to acoustic noise. Participants were required to first encode the stimulus array, maintain a visuo-spatial representation during the delay and then match this sustained representation to the upcoming probe. All of these steps, i.e., encoding, maintenance, and decoding, are affected by noise and cognitive resources (Ma et al., 2014). In the current study, a negative effect of acoustic noise on accuracy was only observed when it was exclusively presented in the delay period. Thus, this effect cannot be caused by a direct influence on perception or matching processes during the stimulus display. Instead, noise either directly affects the population code sustained via interactions of prefrontal and association cortices during the maintenance phase (Sreenivasan et al., 2014), or it indirectly acts on the resources allocated to this process. The absence of this effect in Experiments 2 and 3 could be explained either by a compensatory beneficial effect on encoding or the necessity of white noise to set on during maintenance to be detrimental for performance.

Assuming a mediating role of dopamine, there are two likely explanations for an impairment rather than facilitation caused by white noise. First, an inverted-U shaped relationship has been used to describe behavioral performance as a function of dopamine (Vijayraghavan et al., 2007 Cools and D𠆞sposito, 2011) and noise levels (Usher and Feingold, 2000 Manjarrez et al., 2007 Sikström and Srlund, 2007 Srlund et al., 2007 Mendez-Balbuena et al., 2012 Trenado et al., 2014). Therefore, reduced accuracy in the working memory task can be explained by optimal baseline levels of dopamine or internal noise (Aihara et al., 2008) that may have been reduced by external white noise along the descending arm of the inverted-U shaped function leading to suboptimal performance.

Second, acoustic noise may have enhanced a different facet of working memory, than the one specifically required here. Depending on target site, dopamine has been implicated in different component processes of cognitive control and working memory: while stability and maintenance of information have been argued to be mediated by prefrontal dopamine receptors, flexibility and updating of working memory representations are likely controlled by striatal dopamine receptors (Cools et al., 2007 Cools and D𠆞sposito, 2011). The precise effect of dopamine on gating mechanisms in the striatum, however, remained debated: opening (Braver and Cohen, 2000 Badre, 2012 D𠆚rdenne et al., 2012) as well as locking (Gruber et al., 2006) the gate to working memory has been suggested as a consequence of phasic dopamine release from the SN/VTA. Changes in midbrain activity (Rausch et al., 2013) and putatively associated dopamine transmission caused by white noise administration might modulate cortico–striatal interactions in a way that improves updating at the cost of active maintenance of information, putting the system in a state of enhanced sensitivity to external stimulation and reduced stability of currently held representations in working memory. This would also be consistent with findings of enhanced connectivity between sensory and prefrontal brain areas during auditory noise stimulation (Ward et al., 2010) and noise benefits in sensory detection thresholds (Moss et al., 2004).

What argues against a relationship between dopamine and the detrimental effects of white noise in our working memory paradigm is the absence of a correlation with the dopamine mediated personality traits novelty seeking, exploratory excitability, and reward dependence. Therefore, these accounts remain speculative and need further empirical support. An alternative view is that our results are driven by changes in neurotransmitters other than dopamine (e.g., GABA or norepinephrine see above) or unintended differences between sound conditions. Specifically, white noise has a more abrupt onset than a pure tone with a sinusoidal waveform, resulting in higher startle quality (Combs and Polich, 2006). This, in turn, might lead to a stronger disruption of ongoing encoding or maintenance processes when sound is turned on and off within a trial (as was the case in Experiments 1 and 2) as compared to a condition when it is presented continuously (as was the case in Experiment 3).

Finally, constant difficulty (i.e., working memory load) together with a dichotomous outcome measure (correct vs. incorrect) might result in ceiling effects for some subjects with high working memory capacity. Future studies could circumvent this issue to increase sensitivity by using a task with a parametric or continuous rather than binary outcome measure. This could for instance be the number of retained items out of a larger set of items or the accuracy of retained representations (e.g., continuous report of color or location).

Experiment 4

Reward and white noise differently affected performance in the monetary incentive encoding task: while high potential monetary incentives enhanced recollective memory in the recognition phase, white noise accelerated the speed of perceptual judgments during encoding. An enhancing effect of recognition memory by monetary incentives was observed for recollection but not familiarity, yet, the interaction of incentive value and memory process failed to reach significance. This is in line with a previous study showing reward-driven gains in memory performance for high but not low confidence judgments (Adcock et al., 2006). Given that recollection should be associated with high confidence exclusively, whereas familiarity should reflect varying degrees of confidence (Yonelinas, 2002 Eichenbaum et al., 2007 Yonelinas and Parks, 2007) these results point in a similar direction.

White noise accelerated indoor/outdoor judgments during encoding as compared to silence, but did not affect subsequent recognition memory. This finding concurs with beneficial effects of noise on visual perception (Simonotto et al., 1997 Aihara et al., 2008 Schwarzkopf et al., 2011) and crossmodal stochastic resonance (Manjarrez et al., 2007 Lugo et al., 2008 Gleiss and Kayser, 2014). The current study extends these previous findings from low level signal detection to higher level visual category processing, which depends on lower and higher level visual and association areas along and in proximity to the ventral visual stream (Walther et al., 2009). As has been argued for sensory detection thresholds (Moss et al., 2004), externally applied white noise might boost sensory evidence for visual features toward a threshold for complex category decisions. Such a process could, however, be accomplished at every stage of visual processing, since higher level category processing strongly incorporates low level visual feature extraction (Renninger and Malik, 2004). Therefore, we cannot resolve whether an acceleration of indoor/outdoor judgments by white noise is due to a modulation of early visual processing exclusively or indicates that white noise also acts on category processing in higher visual areas directly.

An enhancement of (higher) sensory processing by white noise is also compatible with a mediating role of the dopaminergic system. For instance, white noise might affect the recruitment and allocation of attentional resources directed by the SN/VTA (Boehler et al., 2011 Krebs et al., 2011) or it might alter the gating of sensory stimuli controlled via cortico–striatal interactions (see above and specifically: Van Schouwenburg et al., 2010). Importantly, an acceleration of indoor/outdoor judgments has not been observed in the absence of reward (Rausch et al., 2013), which recruits the mesolimbic system (Adcock et al., 2006 Bunzeck et al., 2012). Although incentive value did not interact with noise benefit here, white noise might only modulate the speed of perceptual judgments in a context of high motivational state.

Beneficial effects of white noise on long term memory formation (Rausch et al., 2013) and retrieval (Usher and Feingold, 2000) have been reported previously for similar noise levels. However, in our current study, the increase in processing speed caused by white noise did not translate in superior memory formation for the respective pictures. Effects may be overall small in size and easily disrupted by contextual factors, such as motivational state and scanner environment (Rausch et al., 2013).

Experiment 5

Performance in the Posner task was strongly dependent on cue validity. As expected, participants responded faster and more accurately on valid compared to invalid trials. This suggests successful orienting toward the cued location resulting in a processing advantage at that location (Posner, 1980 Posner et al., 1980 Doricchi et al., 2010 Petersen and Posner, 2012). A modulation of this effect by cue probability was at most subtle. Although such an interaction would be in line with assumptions about Bayesian integration in stimulus detection (Knill and Pouget, 2004) and a concrete model of uncertainty in a variant of the Posner task (Yu and Dayan, 2005), it has rarely been investigated empirically and led to inconsistent results (Jonides, 1980 Gottlob et al., 1999).

Participants responded marginally faster during auditory stimulation (for both white noise and pure tone) compared to silence on valid but not invalid trials, resulting in a stronger validity effect. This indicates enhanced processing at the cued location with no costs at the un-cued location. This pattern is inconsistent with faster basic sensorimotor processing (which should accelerate valid and invalid target detection) and a selective effect on orienting of attention (which should produce costs at the un-cued location). Instead, it might emerge if sound enhances two independent processes: one responsible for orienting toward the cued location and the other one responsible for reorienting in trials where no target appeared at that location, thereby counteracting costs at the un-cued location. This would be consistent with assumptions about two independent attention systems guided by dorsal and ventral parietal cortex responsible for orienting and reorienting, respectively (Fox et al., 2006 Corbetta et al., 2008 Vossel et al., 2012). Given the necessary difference in the number of trials in the valid and invalid condition, it is, however, also possible, that effects in invalid trials simply remained undiscovered due to higher error variance in the evaluation of within subject mean RT.

A significant correlation of the personality trait reward dependence with white noise benefit for accuracy did not survive correction for multiple comparisons. Since reward dependence has been linked with the dopaminergic system (Gerra et al., 2000 Krebs et al., 2009), this tentatively supports the claim for inter-individual differences in baseline dopamine levels to determine the effects of acoustic white noise on visual target detection but requires replication to be reasonably interpretable. Moreover, reward dependence has not only been linked to dopamine but also (and initially) to norepinephrine (Cloninger, 1985 Gerra et al., 2000 Ham et al., 2005) making it a rather unspecific marker for inter-individual baseline differences in dopamine levels.


Low-Level Classroom Noise Distracts, Experts Say

By Sarah D. Sparks — January 06, 2015 6 min read

It’s easy to understand why learning may suffer when the teacher’s voice has to compete with a passing 747, but emerging research suggests that quieter noises can have varied effects on student learning and memory.

“It doesn’t take very much sound to really be detrimental to the listeners,” said Gail M. Whitelaw, the director of the Ohio State University Speech-Language-Hearing Clinic in Columbus. “So much of school is auditory, oral learning, and one of the things we know is sound can create more issues with kids with anxiety and attention.”

Low or barely perceptible sound—be it from a lecture in the classroom next door, a heating system that keeps turning on and off, or even a classroom aquarium filter—can increase stress and interfere with memory and learning. Yet it is much less likely to come to the attention of teachers or the students themselves than aircraft or construction noises.

“You can’t depend on the kids to complain,” said Ruth M. Morgan, a speech pathologist at Ephesus Elementary School in Chapel Hill, N.C. “Kids generally go with the flow, and they wouldn’t let you know there’s too much background noise.”

How Loud Is Too Loud?

Noise is measured in decibels on a logarithmic scale every 10 decibels marks an increase in sound that is twice as loud. Normal conversation is usually in the range of 60 to 65 decibels, and children often speak more softly than adults, as low as 35 decibels.

Federal and state guidelines generally recommend that schools dampen sustained sounds of about 90 decibels and above—the level of heavy freeway traffic, for example—which can cause hearing loss if students are exposed to it for extended periods. And federal and state transportation agencies often provide grants to help schools protect their buildings from regular, dangerously loud sounds like a 135-decibel jet takeoff.

Near Chicago’s O’Hare airport, for example, federal and local transportation agencies have spent $350 million to muffle sound at 124 schools, according to the O’Hare Noise Compatibility Commission, an intergovernmental agency in Chicago.

But noise in the background doesn’t have to be that loud to be distracting for students. In a 2013 study in the Journal of Urban Health, a publication of the New York Academy of Medicine, 8- and 9-year-old students who had higher “ambient” noise levels in school performed significantly worse on standardized tests in mathematics and French language, after controlling for their socioeconomic backgrounds. A difference of 10 decibels of regular background noise was associated with 5.5-point-lower scores on average in both subjects.

Similarly, a prior study found students were highly distracted by a television playing in an adjoining room, even when it was barely audible, but they were unable to identify why they were having trouble concentrating.

The results don’t surprise Ms. Morgan in Chapel Hill. She noticed that while the classroom didn’t seem particularly loud, both she and her students seemed to be having trouble following conversations during sessions in which students worked in groups.

“So much of class now is the children speaking to each other, doing buddy reading,” she said. “And children’s voices are softer I was having difficulty hearing them.”

Some sounds are also more vulnerable to distortion: s-, sh-, and ch- sounds in speech are particularly easy to mistake when competing with low-frequency mechanical sounds, such as the hum of a computer fan or heating system.

Ms. Morgan said she thinks her school’s noise issues may be common in older schools, where former “open concept” classrooms were later closed in with walls that typically have less noise insulation than new construction, allowing students to hear more lectures and mechanical sounds in other rooms.

Ms. Morgan downloaded a measuring application for her iPad and checked her room and seven others throughout the building, finding background noise levels of around 60 decibels, just loud enough to compete with conversation. The district eventually paid $1,000 per classroom in the school to install sound systems and to outfit teachers with microphones.

“It does add up it’s kind of expensive, but in the end it’s worth it in terms of student learning,” she said.

Ms. Whitelaw said many schools adopt “solutions” that actually make noise distractions worse, such as adding tennis balls to the legs of desks to change a squeaking sound to a scratching sound when students move. The second sound may be quieter but more annoying.

“We know that noise is really distracting to kids’ attention, and affects kids’ stress levels,” Ms. Whitelaw said.

Repeated studies have found low-volume but chronic ambient noise raises cortisol, a chemical marker of stress, in both children and adults, but younger children are especially sensitive to it. Moreover, intermittent sounds, like a machine that turns on and off throughout the day, can have a stronger effect.

“When kids have high anxiety, and we are adding noise in the classroom, they are struggling to follow the teacher and they are getting exhausted by the end of the day,” Ms. Whitelaw said. “We know that’s a big factor in student performance.”

Noise and Attention

However, some studies are beginning to temper the thought that noise distraction is always bad.

In a study in the spring 2014 Journal of Applied Research in Memory and Cognition , which was discussed at the annual Society for Neuroscience conference in Washington in November, Swedish students were asked to learn texts in either an easy or difficult font, and in either a quiet classroom or one with low background speech—considered one of the most distracting types of sound. Students who had easy-to-read text had more difficulty remembering it when they had learned in a classroom with background speech, but students recalled more of the hard-to-read text when they were also coping with more ambient noise.

“A lot of it is the content of the noise” in comparison to what the student is doing, Ms. Whitelaw said. “If someone is having a conversation behind you, it’s more distracting if the teacher is lecturing, and you find it boring.”

Researchers suggested the students were more aware of the need to concentrate because the text seemed more difficult, and so were better able to “block out” the distractions.

Not every class can be outfitted with microphones or buffered with audio tiles, but Gary William Evans, a professor of human ecology at Cornell University, in Ithaca, N.Y., suggested in the Annual Review of Psychology that it is important for educators and students to be aware of how different noises will affect different types of students.

For example, in a study in the November issue of PLOS-One, researchers at the University of Southampton in England assigned five different tests of working memory—including word recall and recognition tasks, and a game in which students had to push a button or hold back in response to a cue—to 8- to 10-year-old students who had been rated by teachers as having low, normal, or high levels of attentiveness. The students performed the tasks in either a room with a quiet background or one with white noise of varying volumes, from 65 to 85 decibels.

The better that students were initially at paying attention, the worse they were affected by white noise at any level. By contrast, researchers found students with poor attention skills benefited from the additional noise, perhaps for the same reason sounds had helped students in the other survey remember text in a difficult font: The challenge may have sharpened their focus.

“Even if we have to say certain kids have to be in certain environments . the important thing is to know what the environment is: Make a measurement, just so you know what you are starting with,” Ms. Whitelaw said.

“A lot of things teachers think are good can be problems,” Ms. Whitelaw said. “We have teachers say, ‘I put music on to calm kids,’ but I’ve been in classrooms where they have music on pretty much throughout the day, even when there is lecturing, and it really contributes to the ambient noise. We’ve heard music is good, well, but let’s look at the sounds overall.”


Five Ways Colour Can Affect Children in a Learning Environment

With the summer season approaching and bringing with it blue skies and a vast array of colourful flowers, you’ve probably felt the effect of the bright colours on your mood. You may feel happier and generally more positive. But what effects could colour have in a classroom or learning environment?

At a young age we start to associate colours by developing memory, for example, learning that a green banana is not yet ripe, the yellow banana is the ripest and a brown banana is at the end of the ripeness spectrum. By understanding the colour spectrum we are able to recognise its meaning and effects, becoming a vital part of our learning as youngsters.

Children spend the majority of their day in the classroom where colour can be used to enhance and influence their learning. Educators and supply teachers that are passionate about inspiring children can help increase engagement in the classroom by using colour in five easy and effective ways. Take a read below.

What Effect Does Colour Have?

Colour affects your learning by the way your brain functions and uses colour to develop pattern recognition, memory and absorbing new information. It can also visually guide you to locate, compare, understand and recall information faster. In particular, colour affects children’s moods, their behaviour, and educational performance. Here are a few colours and how they can influence learning:

RED – Powerful and attention-grabbing, the colour red creates alertness and excitement. It encourages creativity and can also increase appetite.

BLUE – Suggests calmness, loyalty, peace, serenity, and security, therefore creates a sense of comfort.

YELLOW – Encourages creativity, clarity, and optimism, thus creates positive feelings and improves attention.

GREEN – The colour green symbolises nature and the natural world. It represents balance, growth, tranquillity, cleanliness and calmness. It also can relieve stress and provide a sense of healing.

ORANGE – Considered an energetic colour and similar to red, can increase alertness. Orange creates passion, warmth, excitement and encourages communication.

PINK – Associated with love, romance, nurture, warmth, calmness. and imagination.

Using Colour to Direct Attention

Colour has great importance in enhancing memory performance and one’s visual sense in order to achieve a positive response towards learning. Therefore using colours to emphasise a particular feature or piece of work can increase the attention level of learners: it can also help reduce boredom and increase attention spans.

However, too much use of colour can over-stimulate instead of inspire, so you’ll need to ensure a good balance between bold and neutral colours. The most attention-grabbing colours are warm colours such as red, orange and yellow. Educators need to use more attention-grabbing colours to encourage learning, focus, alertness, and awareness. Cooler colours, such as blue and green tones, can evoke calmness which will stimulate concentration, broader thinking, and conversation.

Implementing Colour Strategically

Colour can enhance the clarity in text by as much as 40% , so it’s important that the learning outcome is achieved by using colour effectively. Strong, bright and bold colours should be used sparingly or with a neutral background to avoid attracting the eye in many directions, thus risking the message becoming lost in the text. Colour can inform and, by improving readability, can help children better understanding the concept of the text they are reading. Use lighter backgrounds that contribute to a higher readability level.

You should consider how you can utilise and implement colour in the classroom itself. For example, providing a quiet place for children in a busy playroom: using shades of soft blues, starry night ceiling and a door that only small people can access. The blue tones can encourage calmness, security, comfort, and peace. This, in effect, can lessen inappropriate behaviour as the children are able to learn to diffuse and deal with their feelings as they take themselves out of situations and relax in the quiet space provided to them.

Colour and Special Educational Needs

Colour can affect all children differently with regards to their mood and behaviour, in particular. those who are sensitive towards colour or struggle with their vision. Children with Autism Spectrum Disorder (ASD) can become stressed by colour and patterns. The choice of colour surrounding them can affect their behaviour, therefore it is essential to create a warm, but not over-stimulating, environment. The level of stimulation should be controlled as autism can typically be affected through extreme sensitivity to the sensory stimulation of sound, light and colour: it’s important to create an appropriately colourful environment for children with ASD.

Colour can be used to support children who are partially sighted. Colours that contrast and provide differentiation between surfaces can help with the perception of size or judging the distance between objects or space. It’s important to understand the level of intensity of the use of a colour particularly for easy identification of different classrooms.

Coloured Furniture in the Classroom

Research has revealed a well-designed classroom can boost learning progress by 16% in reading, writing and maths. Schools or education centres do not often use light coloured furniture because it makes the dirt easy to spot. However, through both research and practical application, it has become clear that colour can have an effect on children’s mood and emotions in a learning environment. It is essential to let the purpose of the room guide the colour scheme selection whether that’s Science, English, Maths or even creating ELearning Spaces to encourage learning. Be creative with the chairs, tables, bookcases, boards, trays, even the carpet and walls to differentiate the importance of each classroom.


Binaural Beats And Memory: Can This Crazy Music Make You Smarter?

It’s a popular perception among many people that listening to binaural beats has a special effect on the brain.

They think binaural beats can help you follow a diet or stop smoking.

Or they think these sounds can amp you up for a competition or calm you down, or even improve memory recall, focus and concentration.

Doesn’t listening to any type of relaxing music have a similar effect?

In this post, we’ll find out if listening to specific frequencies can have a better impact on your mental prowess than listening to Mozart for Pink Floyd!

Yours Free: A Private Course With Cheat Sheets For Becoming A Memory Master, Starting From Scratch.

>>> Click Here For This Special Free Offer.


2 Answers 2

Keep in mind the way they're defining "white noise" in the scientific american article you provided is different from what you link to on wikipedia. The SA definition is more in terms of ambient noise (e.g., traffic, low-level talking, a/c running, etc.) while white noise proper is a signal with a VERY specific acoustical pattern. It seems that the SA article is relating to deterioration in performance due to the stress caused by the increased attentional resources required to "tune-out" the ambient noise. If white noise proper completely eliminates all other ambient noise (without being too loud of course), this eliminates the allocation of these additional resources. Because white noise proper is essentially featureless, one will habituate to it unlike common ambient noise.

Carlson, Rama, Artchakov, & Linnankoski (1997) found a significant decrease in memory when exposed to music during a memory task and a significant increase in performance when exposed to white noise in comparison to a control which had only low level ambient noise. Though it was not the main purpose of the study, the authors conclude that music drew attention away and thus interfered while white noise likely drowned out the ambient noise without drawing attention and thus improved performance. Please keep in mind the sample of this study was on monkeys, but the processes are expected to be generalizable to humans.

Daee & Wilding (1977) found that the likelihood of forgetting during a free recall task is related to the level of noise to which one is exposed during rehearsal such that recall is best in a quiet environment and degrades at 75 and 85 dB. Though this study was not on concentration directly, these results can be seen to have applicable implications regarding attentional resources.

Along these same lines, Salame & Baddeley (1987) found significant differences in recall between unattended speech versus white noise such that unattended speech interferes with performance while no statistical difference was found in the white noise condition (in comparison to a quiet control). The authors conclude ". that noise does not interfere with short-term memory but that unattended speech does impair performance. "

The studies I cite above are related to memory recall tasks which, though involving similar processes to long-term concentration are not perfectly comparable. However, there is a pretty comprehensive literature showing the effects of noise exposure having negative effects on long-term tasks such as learning (e.g., Hygge, 1993, Lercher, Evans, & Meis, 2003). Additionally, Mathews & Canon, 1975 state "data [suggests] that arousal leads to a state of restricted attention or cue utilization in which attention is concentrated on salient features of the setting at the expense of its other aspects" which does not hinder attention to "central or salient events." This idea is related to the theory that noise facilitates functioning through the stimulation of processing such that increased arousal yields better performance until over-arousal occurs which then decreases performance (Hockey, 1983 from Staal, 2004). Stall (2004) also discusses the possibility of continuous v. intermittent noises having differential impact such that continuous may be beneficial while intermittent is harmful, though there is no current agreement in the literature (see pages 88-91).

Thus, the literature seems to support the following:

White noise will improve performance to the extent to which it masks noises that may cause over-arousal or attention shifts away from the task without causing over-arousal itself. Practically speaking, if you're in a quiet environment, white noise is unlikely to have a positive effect on your concentration. If you are in a somewhat noisy environment, white noise will likely have a positive effect. However, in a very noisy environment it will likely have either no or a negative effect.


Effects of Different Sound Waves

The different levels of sound waves can cause different effects on the brain and therefore the overall focus of an individual.

The way the brain works is by the billions of neurons that communicate to each other through electronic waves within it. As neurons fire, they can be affected by the external environment around them.

For example, if you have music on while you exercise, your body and mind will be prone to working out harder.

According to Dr. Jeffery Thompson, sound waves can affect the brain’s waves either positively or negatively. What’s more, the 4 types of brain waves – Alpha, Beta, Delta, and Theta – are prone to getting into sync with any music or sounds around you.

The human brain has a tendency to change its dominant EEG waves towards any external sounds around it. This can be positive and relaxing for some, but stressing for others.

Hypnotic Effects of Certain Sound Waves

Audio sensory can induce hypnosis in certain situations. This is known as binaural beat and it is an auditory illusion.

It can be achieved when two different sine waves with frequencies lower than 1500Hz and fewer than 40Hz between the two, are placed in each ear.

For example, if your right ear is listening to 1400Hz and your left ear is listening to 1370Hz, you can achieve this effect because your brain will automatically pick up a third tone – the binaural beat.

When the brain hears a binaural beat, it can cause an individual to feel hypnotized by the sound.

In comparison, of EEG’s brains that are listening to binaural beats and those that are experiencing meditation have nearly the exact same readings on the EEG charts.

White Noise for Maximizing Focus

White noise can provide a soothing and relaxing background noise, which can maximize your overall focus. There are different levels of ‘white’ noise which can include pink noise, white noise, and brown noise just to name a few.

When you are interested in improving your ability to concentrate, these different types of white noise can provide the stimulus your brain needs to focus, by delivering just the right amount of sound without the distraction of lyrics or intense musical beats.

The right kind of white noise can help relax your brain while still allowing you to hone your focus on the task in front of you.

If having background noise is something you enjoy and you want to increase your focus, try out the different degrees of white noise to find the one that will work best for you and your brain.

Sounds and focus directly correlate to your productivity. Finding the right balance of either silence, white noise, or stimulating music, can be crucial to your focus and therefore, your productivity.

Each and every one of us has a differently wired brain and sound will affect us differently, so it’s up to you to find what works best for your focus – silence, white noise, or your favorite songs.

Are you struggling with finding focus? Have you recently tried white noise? Let us know about your experience!

About The Author

This article is written by Sarah, the editor of Headphone Selection, which helps you choose the best headphones. She loves all sound technology and firmly believes in the power of positive music.

Looking for something?
Hey, I’m Lidiya

Thanks for stopping by. I’m Lidiya, a blogger, course creator and founder of Let’s Reach Success.

I help high vibe women create an abundant, value-driven business so they can live a fearless life and provide epic value.


Reading People: Behavioral Anomalies and Investigative Interviewing

While interviewing a crime suspect a police officer asks what happened. For an instant the interviewee’s eyes get wide so that the white above the irises is visible. The suspect’s story begins with details about memories from before the incident, including things the alleged offender did and did not do. The suspected criminal describes the event while wringing the hands and looking away, up and to the left, not making direct eye contact. The interviewee’s speech becomes slower and references to other people change with the use of pronouns. The suspect, whose left eyebrow is twitching, does not speak about the incident itself and finishes the story with “and that's about it.” 

The description above makes much of this individual’s story suspicious from a credibility assessment standpoint. However, when conducting interviews, investigators must ask themselves some important questions based on their observation of behavioral anomalies.                              

  • What cues contribute to the determination, and why?
  • Which behaviors are meaningful signs, and which are not?
  • Which actions are true signals of something important, and which are just noise?
  • Which signs provide guidelines for further probing and questioning?
  • What insights can be gained from the observed indicators, and why?

Many law enforcement professionals understand and appreciate the importance of behavioral anomalies. These verbal and nonverbal signs of cognitions and emotions provide additional clues to what an individual is thinking and feeling beyond the content of the words being spoken. In the context of investigative interviewing, these behavioral anomalies are called indicators.

These anomalies provide important cues and valuable insight into the personality, motivation, and intention of suspects. They can be signs of hostile intent, suspicious behavior, veracity or lying, or topics and concerns that are important to the interviewee. These crucial bits of knowledge give investigators information superiority that can guide them through the process and help them complete interviews. Individuals typically do not know that they are revealing these indicators.

Dr. Matsumoto is a professor of psychology at San Francisco State University and director of a private training and consulting firm in California. 

Ms. Skinner is a retired FBI Supervisory Special Agent and former instructor at the FBI Academy in Quantico, Virginia.

Dr. Hwang is a research scientist and vice president of a private training and consulting firm in California.

When reading people, one important distinction interviewers must make is the difference between validated and nonvalidated indicators. Those that are validated have scientific and field evidence documenting the association between the behavior and specific cognitions or emotions. These anomalies are laboratory tested under strict scientific conditions and vetted in the field by practitioners. Nonvalidated indicators lack such data—either in scientific evidence, field operations, or both. 1

Validation provides evidence for accuracy and consistency across various people in different contexts. Noticing that a suspect’s hands were held in a certain way when describing an incident that later turned out to be a lie is not evidence that the behavior is indicative of lying for other people in varying situations. Observation alone is not sufficient to label a certain behavior as a validated indicator because it has not withstood the scrutiny of rigorous testing in the laboratory and the field. Such testing would require establishing the conditions in which the indicator may or may not occur with multiple people. If the behavior ensued that would be evidence for its validation, and if it did not that would be verification for its nonvalidation.

There are validated and nonvalidated indicators imbedded in the example at the beginning of this article. The flash of the eyes so that the white above the iris is seen is a validated indicator of concealed fear, and the suspect’s comments about behavior that did not occur are indicative of a potential lie. Looking up to the left and twitching of the left eyebrow are not validated indicators of lying, even though many people believe they are.

Programs that teach nonvalidated indicators produce negative results in people’s ability to detect lies from truths. 2 For example, a common belief is that a lack of eye contact is an indicator of lying however, numerous studies have tested this and most do not support it. Therefore, this belief is more myth than reality. 3 A recent study showed that liars know this too and compensate for it by looking the interviewer straight in the eye more than truth tellers. 4

There are two categories of validated behavioral indicators that are relevant to interrogations. One involves linguistic markers used in words when individuals provide statements or answer questions. This category is entirely verbal—based on principles of human memory and recall—and suggests that lies are different from truths in their demands upon memory, which is reflected by changes in grammar and language. Research has indicated that lies comprise fewer words and more omissions of information are less plausible, structured, and logical are more discrepant and ambivalent contain repeated details lack contextual imbedding and include more descriptions of what did not occur. 5 These findings lead to specific linguistic and grammatical indicators of veracity and lying—such as the use of negation, extraneous information, and different types of adverbs—that may be identified in statements and interviews.

The second category includes nonverbal behaviors (NVB). Research has shown that various emotions and cognitions are communicated through facial expression, voice tone, gesture, body movement, and posture. 6 In the investigative context, NVB indicators occur because conflicting thoughts and feelings transpire when people lie and are under stress but attempt to hide their feelings and expressions. These anomalies often leak out nonverbally. Research has established that NVB indicators of lying include changes in the use of speech illustrators and symbolic gestures subtle and microfacial manifestations of facial expressions variations in blinking, pauses, and speech rates and outward attempts to regulate emotions. 7

It is possible to train individuals to identify verbal and nonverbal indicators of truthfulness and lying. Verbal indicators are acknowledged through analysis of specific linguistic markers and words using Statement Analysis (SA)—also known as Statement Validity Analysis, Criteria-Based Content Analysis, Reality Monitoring, and Scientific Content Analysis. 8 Nonverbal indicators are identified as subtle or microfacial expressions of emotion, gestures, vocal changes, and body language. 9

Statement and nonverbal analysis are not new to law enforcement as the techniques have been taught to investigators for years. However, in real-life, indicators of veracity and lying occur simultaneously, and awareness of both increases an investigator’s ability to identify meaningful content areas of an interview detect clues to deceit and provide additional insight into the thoughts, feelings, personality, and motivation of the interviewee. People sometimes produce verbal indicators with no NVB and NVB indicators without talking. Investigators who pay attention solely to one or the other may miss valuable information.

The importance of considering verbal and nonverbal indicators concurrently was highlighted in a recent study—published in the FBI Law Enforcement Bulletin—that examined the combined contributions to the prediction of deception or truthfulness. 10 The study showed that members of ideologically-motivated groups committed one of two types of lies. In one, participants were placed in a situation where they could commit a crime—steal $50 in cash from a briefcase—and later were interviewed about whether they carried out the crime or not (the crime scenario). In another setting, individuals chose to lie or tell the truth about their beliefs concerning their political cause (the opinion scenario). Regardless of the circumstances, there were stakes involved—if they were judged as lying, they would lose their participation fee and face one hour of white noise blasts while sitting on a cold, steel chair in a small, cramped room.

Videos of 20 individuals󈟚 each from the crime and opinion scenarios, half truth tellers and half liars—were analyzed. Analyses of their words and NVB together led to a 90 percent accuracy rate for classifying the individuals as lying or telling the truth. Compared to the average accuracy rate of 53 percent—no better than chance—by observers in previous studies, the findings indicated that behavioral anomalies in verbal statements and NVB collectively provided a better source for determining veracity and deceit than basic observation. 11

Investigators gained valuable information within 40 seconds of an interview with a 42-year-old female suspect who allegedly assaulted a minor. After officers Mirandized and obtained background information from the suspected perpetrator the discussion ensued—nonverbal behaviors are italicized.

The investigator asked, “Mary, do you know the reason why you’re here today?”

Mary replied, “I have no idea.” She smiled, leaned forward, and showed concern on her face. Her voice sounded vulnerable.

The investigator said, “Okay…the reason why you’re here today is that an allegation has been made on you…”

Mary responded, “Okay.” She spoke softly while nodding her head.

The investigator continued, “…that you assaulted Joe.”

Mary’s brows went up and her eyes opened wide so that the whites above the eyes could be seen. Her jaw dropped and her mouth opened.

The investigator asked, “Do you know who Joe is?”

Mary replied, “I have no idea.” She shook her head quickly and gave a brief microfacial expression of disgust.

The investigator said, “Joe lives down the street from you.”

Mary (displaying another microfacial expression of disgust) asked, “What?” She spoke incredulously, leaned forward, and smiled.

The investigator inquired, “An allegation came out that you assaulted him. He’s 13 years old. I’m just going to point blank ask you, did you have anything to do with it?”

Mary (smiling) responded, “No. He was definitely hitting on…. It was one night when they spent the night over (smiling) and he was acting kind of strange that night and nothing happened.”

At the beginning when Mary was asked if she knew why she was in the interview, Mary smiled, leaned forward, looked concerned, and said in a vulnerable voice, “I have no idea.” Her coy, almost flirtatious demeanor suggested that this may be a major characteristic of her personality. Mary said “Okay” when the investigator stated that an allegation had been made about her. This implied that she knew what the investigator was talking about and could speak to her participation in the incident. It also could have indicated that Mary merely was tracking the conversation by acknowledging what was being said—known as back-channel communication. Knowing her baseline would help the investigator make this distinction.

Mary’s eyes widening for an instant indicated fear, suggesting that she was afraid of something but trying to control her outward display—as opposed to someone who was innocent but afraid of being misbelieved, in which case the fear would not be displayed as a microexpression. When Mary said that she had no idea who Joe was but exhibited two microexpressions of disgust, this suggested that she knew exactly who Joe was—part of her brain was processing information that was incongruent with what she was saying. She then revealed that she did know Joe, despite having just denied it, by stating, “He was definitely hitting on…” before she stopped herself. Mary saying “It was one night…” indicated that this was an incident she knew about. When Mary tried to stop the conversation by saying that “nothing happened” this signified that something actually had happened, but she was omitting the facts.

This example demonstrates how verbal and nonverbal indicators of veracity and deceit occur simultaneously during communication. They are woven into the ongoing interaction and convey a wealth of information above and beyond the surface meaning of the words. It would benefit officers to identify these indicators when conducting interviews. Their detection provides valuable assistance for guiding the investigator to meaningful content areas, helping build cases strategically and tactically, developing themes for use in interrogations, and arriving at ground truth quickly and accurately.

The techniques for both statement and NVB analysis typically have been taught separately to law enforcement officers, providing them with increased skill in one particular technique but resulting in their missing much of the useful information that interviewees impart. A few years ago the FBI National Academy (NA) began offering a course on investigative interviewing that united the techniques of statement and NVB analysis. Merging these techniques into a single application was a risk however, it was possible that training in both could produce an information overload such that their practical application would have been unsuccessful. Trainees learning both techniques independently often reported that they were overwhelmed by the amount of detail to which they had to attend. Fortunately, combining the techniques produced positive results and the benefit of more real-life circumstances.

Mid-to-upper-level career law enforcement officers concurrently enrolled in two courses—one was a traditional course on statement analysis (trainees had to learn the basics of SA) and the other was a combined SA and NVB analysis course. Both courses covered validated indicators of truthfulness and lying culled from research and included lectures, discussions, video reviews, group projects, and individual practicum. After learning the basic principles of both statement and NVB analysis, trainees practiced on realistic source materials—actual statements and videos of suspects, witnesses, and informants telling truths and lies—to hone their skills. The combined course also required trainees to learn how to recognize microfacial expressions of emotion.

By the end of the courses, trainees had improved their capacity to recognize verbal and nonverbal indicators of veracity and deceit and to incorporate those skills into their interview strategies. Pre- and post-test data on their ability to detect truths from a standardized set of videos were obtained in three sessions. At the beginning of the courses, attendees viewed a set of 10 videos prior to any training in SA or NVB analysis. Participants watched a different set of 10 videos at the end of the courses. The videos were switched across both courses so that any findings were not specific to one set. A sizable increase in accuracy rates—between 10 and 25 percent—in the trainees’ ability to detect lies from truths resulted (Figure 1). These improvement rates were remarkable since the test videos lasted only 60 to 90 seconds. If the trainees had been able to question the interviewees in person, in a longer interview, with other typically available sources of evidence—forensics, witness statements, and physical evidence—the increase could have led to substantial differences in the efficacy by which investigators obtain ground truth and close cases.

Figure 1 - Accuracy Rates Before and After Training, Separately for All Videos and Crime Videos Only

Although trainees initially reported being overwhelmed by the details, they expressed greater comfort with the techniques by the end of the sessions. Many students reported that after learning and applying both statement and nonverbal behavior analysis they recognized so many indicators that too many potential clues providing insight into interviewees’ minds became apparent. They had to prioritize and determine which ones to act on, thereby producing the collateral benefit of improving their thinking about interrogation strategies and tactics.

Behavioral anomalies—the verbal and nonverbal indicators of veracity and deceit—occur simultaneously in real-life. Recognizing these indicators helps investigators detect lies and gain insight into the personality, motivation, and internal conflicts of interviewees and identify content areas necessitating further exploration and discovery. Law enforcement officers must imbed these techniques within their strategic interview methodology.

Behavioral anomalies are signs investigators can use to determine truth however, they should not be interpreted strictly given that research has not identified any behavior or behavior combinations that are unique to lying. 12 They are highly dependent upon the interviewer’s skills and should be used strictly as a means to an end.

Using behavioral anomalies in investigative interviewing will not solve every case. Interviews should be augmented by witness statements, forensics, and other evidence. Investigators must prepare and plan for interviews, develop questions, and guide discussions as they recognize indicators. Those who have lie detection training must be cautious of post-training biases. 13 However, identifying valid indicators—both verbal and nonverbal—remains a useful tool for any law enforcement investigator.

Additional information may be obtained from the authors at [email protected], [email protected], or [email protected] 

1  There are different types of nonvalidated indicators. For example, potential indicators that have never been tested scientifically should be considered unvalidated indicators. Potential indicators that have been tested scientifically but did not produce reliable findings would be considered invalidated indicators. For the purposes of this article, both are called nonvalidated indicators.


Discussion

Previous work on noise benefits in neural processing and cognition has highlighted different, albeit not mutually exclusive, underlying mechanisms. Closely related to the physical concept of stochastic resonance (Gammaitoni et al., 1998), it has been stated that an optimal level of noise added to a subthreshold sensory signal can cause threshold crossing and thus enhance sensitivity for weak signals (Douglass et al., 1993 Collins et al., 1995 Wiesenfeld and Moss, 1995 Zeng et al., 2000 Moss et al., 2004). Moreover, noise has been linked to intra- and interregional neural synchronization (Moss et al., 2004 Ward et al., 2010). And finally, based on psychopathology research (Sikström and Srlund, 2007), a link has been suggested between noise benefits and dopaminergic neuromodulation. By altering the ratio of tonic and phasic activity in the dopaminergic midbrain (i.e., SN/VTA) and its connectivity with higher cortical areas (i.e., superior temporal sulcus) (Rausch et al., 2013), externally applied noise might act on salience assessment (Redgrave et al., 1999 Horvitz, 2000), resource allocation (Boehler et al., 2011 Krebs et al., 2011), and cortical signal-to-noise ratio (Mattay et al., 1996, 2003 Li et al., 2001 Mattay et al., 2002 Winterer and Weinberger, 2004 Kroener et al., 2009). Other neurochemical systems such as GABA or norepinephrine, however, might also be involved (Coull et al., 2004 Samoudi et al., 2012).

The current study investigated the effects of acoustic white noise on attentional and mnemonic processes that strongly depend on dopaminergic signaling. Performance in a change detection task, a monetary incentive encoding task, and the Posner task was compared for concurrently presented white noise, a pure tone, and silence. Sound levels of 70dB were chosen based on previous studies showing an effectiveness of similar noise levels in improving mnemonic functions (Usher and Feingold, 2000 Rausch et al., 2013), although it should be noted, that some studies used slightly higher noise levels at around 75� dB (e.g., Carlson et al., 1997 Srlund et al., 2010). Since, in the current study, pleasantness of pure tone and white noise were both rated slightly aversive on average (and strongly aversive by some subjects) already at 70 dB, we, however, suggest being careful when applying higher sound levels for an extended time period without individual adjustment. We hypothesized that white noise but not a pure tone would increase performance and that beneficial effects would correlate with personality dimensions known to be associated with interindividual differences in dopaminergic system parameters. These predictions could not be fully confirmed, leaving the modulatory influence of noise on higher cognitive functions a subject for further investigations.

Experiments 1𠄳

Contrary to our expectation, working memory performance was impaired when white noise was presented in the delay period of a delay-match-to-sample task. This effect was selective for white noise and not a general effect of auditory stimulation, since the pure tone did not affect performance. This finding is in contrast to previously shown beneficial effects of white noise on working memory performance in monkeys (Carlson et al., 1997), but resembles deteriorating effects of white noise on memory for verbal sentences in healthy controls (Srlund et al., 2007).

The systematic variation of sound presentation in Experiments 1𠄳 makes it possible to localize a time period and the associated cognitive function sensitive to acoustic noise. Participants were required to first encode the stimulus array, maintain a visuo-spatial representation during the delay and then match this sustained representation to the upcoming probe. All of these steps, i.e., encoding, maintenance, and decoding, are affected by noise and cognitive resources (Ma et al., 2014). In the current study, a negative effect of acoustic noise on accuracy was only observed when it was exclusively presented in the delay period. Thus, this effect cannot be caused by a direct influence on perception or matching processes during the stimulus display. Instead, noise either directly affects the population code sustained via interactions of prefrontal and association cortices during the maintenance phase (Sreenivasan et al., 2014), or it indirectly acts on the resources allocated to this process. The absence of this effect in Experiments 2 and 3 could be explained either by a compensatory beneficial effect on encoding or the necessity of white noise to set on during maintenance to be detrimental for performance.

Assuming a mediating role of dopamine, there are two likely explanations for an impairment rather than facilitation caused by white noise. First, an inverted-U shaped relationship has been used to describe behavioral performance as a function of dopamine (Vijayraghavan et al., 2007 Cools and D𠆞sposito, 2011) and noise levels (Usher and Feingold, 2000 Manjarrez et al., 2007 Sikström and Srlund, 2007 Srlund et al., 2007 Mendez-Balbuena et al., 2012 Trenado et al., 2014). Therefore, reduced accuracy in the working memory task can be explained by optimal baseline levels of dopamine or internal noise (Aihara et al., 2008) that may have been reduced by external white noise along the descending arm of the inverted-U shaped function leading to suboptimal performance.

Second, acoustic noise may have enhanced a different facet of working memory, than the one specifically required here. Depending on target site, dopamine has been implicated in different component processes of cognitive control and working memory: while stability and maintenance of information have been argued to be mediated by prefrontal dopamine receptors, flexibility and updating of working memory representations are likely controlled by striatal dopamine receptors (Cools et al., 2007 Cools and D𠆞sposito, 2011). The precise effect of dopamine on gating mechanisms in the striatum, however, remained debated: opening (Braver and Cohen, 2000 Badre, 2012 D𠆚rdenne et al., 2012) as well as locking (Gruber et al., 2006) the gate to working memory has been suggested as a consequence of phasic dopamine release from the SN/VTA. Changes in midbrain activity (Rausch et al., 2013) and putatively associated dopamine transmission caused by white noise administration might modulate cortico–striatal interactions in a way that improves updating at the cost of active maintenance of information, putting the system in a state of enhanced sensitivity to external stimulation and reduced stability of currently held representations in working memory. This would also be consistent with findings of enhanced connectivity between sensory and prefrontal brain areas during auditory noise stimulation (Ward et al., 2010) and noise benefits in sensory detection thresholds (Moss et al., 2004).

What argues against a relationship between dopamine and the detrimental effects of white noise in our working memory paradigm is the absence of a correlation with the dopamine mediated personality traits novelty seeking, exploratory excitability, and reward dependence. Therefore, these accounts remain speculative and need further empirical support. An alternative view is that our results are driven by changes in neurotransmitters other than dopamine (e.g., GABA or norepinephrine see above) or unintended differences between sound conditions. Specifically, white noise has a more abrupt onset than a pure tone with a sinusoidal waveform, resulting in higher startle quality (Combs and Polich, 2006). This, in turn, might lead to a stronger disruption of ongoing encoding or maintenance processes when sound is turned on and off within a trial (as was the case in Experiments 1 and 2) as compared to a condition when it is presented continuously (as was the case in Experiment 3).

Finally, constant difficulty (i.e., working memory load) together with a dichotomous outcome measure (correct vs. incorrect) might result in ceiling effects for some subjects with high working memory capacity. Future studies could circumvent this issue to increase sensitivity by using a task with a parametric or continuous rather than binary outcome measure. This could for instance be the number of retained items out of a larger set of items or the accuracy of retained representations (e.g., continuous report of color or location).

Experiment 4

Reward and white noise differently affected performance in the monetary incentive encoding task: while high potential monetary incentives enhanced recollective memory in the recognition phase, white noise accelerated the speed of perceptual judgments during encoding. An enhancing effect of recognition memory by monetary incentives was observed for recollection but not familiarity, yet, the interaction of incentive value and memory process failed to reach significance. This is in line with a previous study showing reward-driven gains in memory performance for high but not low confidence judgments (Adcock et al., 2006). Given that recollection should be associated with high confidence exclusively, whereas familiarity should reflect varying degrees of confidence (Yonelinas, 2002 Eichenbaum et al., 2007 Yonelinas and Parks, 2007) these results point in a similar direction.

White noise accelerated indoor/outdoor judgments during encoding as compared to silence, but did not affect subsequent recognition memory. This finding concurs with beneficial effects of noise on visual perception (Simonotto et al., 1997 Aihara et al., 2008 Schwarzkopf et al., 2011) and crossmodal stochastic resonance (Manjarrez et al., 2007 Lugo et al., 2008 Gleiss and Kayser, 2014). The current study extends these previous findings from low level signal detection to higher level visual category processing, which depends on lower and higher level visual and association areas along and in proximity to the ventral visual stream (Walther et al., 2009). As has been argued for sensory detection thresholds (Moss et al., 2004), externally applied white noise might boost sensory evidence for visual features toward a threshold for complex category decisions. Such a process could, however, be accomplished at every stage of visual processing, since higher level category processing strongly incorporates low level visual feature extraction (Renninger and Malik, 2004). Therefore, we cannot resolve whether an acceleration of indoor/outdoor judgments by white noise is due to a modulation of early visual processing exclusively or indicates that white noise also acts on category processing in higher visual areas directly.

An enhancement of (higher) sensory processing by white noise is also compatible with a mediating role of the dopaminergic system. For instance, white noise might affect the recruitment and allocation of attentional resources directed by the SN/VTA (Boehler et al., 2011 Krebs et al., 2011) or it might alter the gating of sensory stimuli controlled via cortico–striatal interactions (see above and specifically: Van Schouwenburg et al., 2010). Importantly, an acceleration of indoor/outdoor judgments has not been observed in the absence of reward (Rausch et al., 2013), which recruits the mesolimbic system (Adcock et al., 2006 Bunzeck et al., 2012). Although incentive value did not interact with noise benefit here, white noise might only modulate the speed of perceptual judgments in a context of high motivational state.

Beneficial effects of white noise on long term memory formation (Rausch et al., 2013) and retrieval (Usher and Feingold, 2000) have been reported previously for similar noise levels. However, in our current study, the increase in processing speed caused by white noise did not translate in superior memory formation for the respective pictures. Effects may be overall small in size and easily disrupted by contextual factors, such as motivational state and scanner environment (Rausch et al., 2013).

Experiment 5

Performance in the Posner task was strongly dependent on cue validity. As expected, participants responded faster and more accurately on valid compared to invalid trials. This suggests successful orienting toward the cued location resulting in a processing advantage at that location (Posner, 1980 Posner et al., 1980 Doricchi et al., 2010 Petersen and Posner, 2012). A modulation of this effect by cue probability was at most subtle. Although such an interaction would be in line with assumptions about Bayesian integration in stimulus detection (Knill and Pouget, 2004) and a concrete model of uncertainty in a variant of the Posner task (Yu and Dayan, 2005), it has rarely been investigated empirically and led to inconsistent results (Jonides, 1980 Gottlob et al., 1999).

Participants responded marginally faster during auditory stimulation (for both white noise and pure tone) compared to silence on valid but not invalid trials, resulting in a stronger validity effect. This indicates enhanced processing at the cued location with no costs at the un-cued location. This pattern is inconsistent with faster basic sensorimotor processing (which should accelerate valid and invalid target detection) and a selective effect on orienting of attention (which should produce costs at the un-cued location). Instead, it might emerge if sound enhances two independent processes: one responsible for orienting toward the cued location and the other one responsible for reorienting in trials where no target appeared at that location, thereby counteracting costs at the un-cued location. This would be consistent with assumptions about two independent attention systems guided by dorsal and ventral parietal cortex responsible for orienting and reorienting, respectively (Fox et al., 2006 Corbetta et al., 2008 Vossel et al., 2012). Given the necessary difference in the number of trials in the valid and invalid condition, it is, however, also possible, that effects in invalid trials simply remained undiscovered due to higher error variance in the evaluation of within subject mean RT.

A significant correlation of the personality trait reward dependence with white noise benefit for accuracy did not survive correction for multiple comparisons. Since reward dependence has been linked with the dopaminergic system (Gerra et al., 2000 Krebs et al., 2009), this tentatively supports the claim for inter-individual differences in baseline dopamine levels to determine the effects of acoustic white noise on visual target detection but requires replication to be reasonably interpretable. Moreover, reward dependence has not only been linked to dopamine but also (and initially) to norepinephrine (Cloninger, 1985 Gerra et al., 2000 Ham et al., 2005) making it a rather unspecific marker for inter-individual baseline differences in dopamine levels.


Five Ways Colour Can Affect Children in a Learning Environment

With the summer season approaching and bringing with it blue skies and a vast array of colourful flowers, you’ve probably felt the effect of the bright colours on your mood. You may feel happier and generally more positive. But what effects could colour have in a classroom or learning environment?

At a young age we start to associate colours by developing memory, for example, learning that a green banana is not yet ripe, the yellow banana is the ripest and a brown banana is at the end of the ripeness spectrum. By understanding the colour spectrum we are able to recognise its meaning and effects, becoming a vital part of our learning as youngsters.

Children spend the majority of their day in the classroom where colour can be used to enhance and influence their learning. Educators and supply teachers that are passionate about inspiring children can help increase engagement in the classroom by using colour in five easy and effective ways. Take a read below.

What Effect Does Colour Have?

Colour affects your learning by the way your brain functions and uses colour to develop pattern recognition, memory and absorbing new information. It can also visually guide you to locate, compare, understand and recall information faster. In particular, colour affects children’s moods, their behaviour, and educational performance. Here are a few colours and how they can influence learning:

RED – Powerful and attention-grabbing, the colour red creates alertness and excitement. It encourages creativity and can also increase appetite.

BLUE – Suggests calmness, loyalty, peace, serenity, and security, therefore creates a sense of comfort.

YELLOW – Encourages creativity, clarity, and optimism, thus creates positive feelings and improves attention.

GREEN – The colour green symbolises nature and the natural world. It represents balance, growth, tranquillity, cleanliness and calmness. It also can relieve stress and provide a sense of healing.

ORANGE – Considered an energetic colour and similar to red, can increase alertness. Orange creates passion, warmth, excitement and encourages communication.

PINK – Associated with love, romance, nurture, warmth, calmness. and imagination.

Using Colour to Direct Attention

Colour has great importance in enhancing memory performance and one’s visual sense in order to achieve a positive response towards learning. Therefore using colours to emphasise a particular feature or piece of work can increase the attention level of learners: it can also help reduce boredom and increase attention spans.

However, too much use of colour can over-stimulate instead of inspire, so you’ll need to ensure a good balance between bold and neutral colours. The most attention-grabbing colours are warm colours such as red, orange and yellow. Educators need to use more attention-grabbing colours to encourage learning, focus, alertness, and awareness. Cooler colours, such as blue and green tones, can evoke calmness which will stimulate concentration, broader thinking, and conversation.

Implementing Colour Strategically

Colour can enhance the clarity in text by as much as 40% , so it’s important that the learning outcome is achieved by using colour effectively. Strong, bright and bold colours should be used sparingly or with a neutral background to avoid attracting the eye in many directions, thus risking the message becoming lost in the text. Colour can inform and, by improving readability, can help children better understanding the concept of the text they are reading. Use lighter backgrounds that contribute to a higher readability level.

You should consider how you can utilise and implement colour in the classroom itself. For example, providing a quiet place for children in a busy playroom: using shades of soft blues, starry night ceiling and a door that only small people can access. The blue tones can encourage calmness, security, comfort, and peace. This, in effect, can lessen inappropriate behaviour as the children are able to learn to diffuse and deal with their feelings as they take themselves out of situations and relax in the quiet space provided to them.

Colour and Special Educational Needs

Colour can affect all children differently with regards to their mood and behaviour, in particular. those who are sensitive towards colour or struggle with their vision. Children with Autism Spectrum Disorder (ASD) can become stressed by colour and patterns. The choice of colour surrounding them can affect their behaviour, therefore it is essential to create a warm, but not over-stimulating, environment. The level of stimulation should be controlled as autism can typically be affected through extreme sensitivity to the sensory stimulation of sound, light and colour: it’s important to create an appropriately colourful environment for children with ASD.

Colour can be used to support children who are partially sighted. Colours that contrast and provide differentiation between surfaces can help with the perception of size or judging the distance between objects or space. It’s important to understand the level of intensity of the use of a colour particularly for easy identification of different classrooms.

Coloured Furniture in the Classroom

Research has revealed a well-designed classroom can boost learning progress by 16% in reading, writing and maths. Schools or education centres do not often use light coloured furniture because it makes the dirt easy to spot. However, through both research and practical application, it has become clear that colour can have an effect on children’s mood and emotions in a learning environment. It is essential to let the purpose of the room guide the colour scheme selection whether that’s Science, English, Maths or even creating ELearning Spaces to encourage learning. Be creative with the chairs, tables, bookcases, boards, trays, even the carpet and walls to differentiate the importance of each classroom.


One explanation is that different people need different amounts of noise for optimal arousal and optimal performance.

Stochastic resonance is a natural phenomenon, whereby a certain amount of noise improves the ability to detect a signal. By introducing noise, signals that are below the perception threshold are boosted enough so that they can be perceived. For example, adding a certain amount of auditory noise allows you to hear sounds that were previously undetectable by your ears.

If you add too much noise though, you decrease the signal-to-noise ratio the louder the noise the more you drown out the sound in the end, it becomes indiscernible in the noise. This is how sound masking works. So there can be too little and too much noise!

Stochastic resonance can be observed in many different domains. This also includes our brain’s neural systems:

The researchers in the above-mentioned studies suggest that inattentive people might have too little noise in their neural systems. By adding white noise, their brain is pushed towards optimal arousal and better cognitive functioning. At the same time, people who are already optimally aroused are getting overstimulated by the white noise.

The amount of noise needed for optimal arousal varies from person to person.

In a very recent study, exposed to white noise played through headphones at 80 dB(A), children suffering from ADHD showed a much improved visual working memory and verbal recall ability compared to a quiet control condition. Their performance approached that of typically developed children whose performance declined slightly (but not significantly) under white noise. In that particular experiment, white noise was more effective than ADHD medication!

I would argue that the amount of noise needed for optimal arousal varies even in a single person, for example, depending on the time of the day, nutrition, and the amount of sleep they have had.

Last night, I only slept 5 hours, and today – white noise helps me to stay awake!


Low-Level Classroom Noise Distracts, Experts Say

By Sarah D. Sparks — January 06, 2015 6 min read

It’s easy to understand why learning may suffer when the teacher’s voice has to compete with a passing 747, but emerging research suggests that quieter noises can have varied effects on student learning and memory.

“It doesn’t take very much sound to really be detrimental to the listeners,” said Gail M. Whitelaw, the director of the Ohio State University Speech-Language-Hearing Clinic in Columbus. “So much of school is auditory, oral learning, and one of the things we know is sound can create more issues with kids with anxiety and attention.”

Low or barely perceptible sound—be it from a lecture in the classroom next door, a heating system that keeps turning on and off, or even a classroom aquarium filter—can increase stress and interfere with memory and learning. Yet it is much less likely to come to the attention of teachers or the students themselves than aircraft or construction noises.

“You can’t depend on the kids to complain,” said Ruth M. Morgan, a speech pathologist at Ephesus Elementary School in Chapel Hill, N.C. “Kids generally go with the flow, and they wouldn’t let you know there’s too much background noise.”

How Loud Is Too Loud?

Noise is measured in decibels on a logarithmic scale every 10 decibels marks an increase in sound that is twice as loud. Normal conversation is usually in the range of 60 to 65 decibels, and children often speak more softly than adults, as low as 35 decibels.

Federal and state guidelines generally recommend that schools dampen sustained sounds of about 90 decibels and above—the level of heavy freeway traffic, for example—which can cause hearing loss if students are exposed to it for extended periods. And federal and state transportation agencies often provide grants to help schools protect their buildings from regular, dangerously loud sounds like a 135-decibel jet takeoff.

Near Chicago’s O’Hare airport, for example, federal and local transportation agencies have spent $350 million to muffle sound at 124 schools, according to the O’Hare Noise Compatibility Commission, an intergovernmental agency in Chicago.

But noise in the background doesn’t have to be that loud to be distracting for students. In a 2013 study in the Journal of Urban Health, a publication of the New York Academy of Medicine, 8- and 9-year-old students who had higher “ambient” noise levels in school performed significantly worse on standardized tests in mathematics and French language, after controlling for their socioeconomic backgrounds. A difference of 10 decibels of regular background noise was associated with 5.5-point-lower scores on average in both subjects.

Similarly, a prior study found students were highly distracted by a television playing in an adjoining room, even when it was barely audible, but they were unable to identify why they were having trouble concentrating.

The results don’t surprise Ms. Morgan in Chapel Hill. She noticed that while the classroom didn’t seem particularly loud, both she and her students seemed to be having trouble following conversations during sessions in which students worked in groups.

“So much of class now is the children speaking to each other, doing buddy reading,” she said. “And children’s voices are softer I was having difficulty hearing them.”

Some sounds are also more vulnerable to distortion: s-, sh-, and ch- sounds in speech are particularly easy to mistake when competing with low-frequency mechanical sounds, such as the hum of a computer fan or heating system.

Ms. Morgan said she thinks her school’s noise issues may be common in older schools, where former “open concept” classrooms were later closed in with walls that typically have less noise insulation than new construction, allowing students to hear more lectures and mechanical sounds in other rooms.

Ms. Morgan downloaded a measuring application for her iPad and checked her room and seven others throughout the building, finding background noise levels of around 60 decibels, just loud enough to compete with conversation. The district eventually paid $1,000 per classroom in the school to install sound systems and to outfit teachers with microphones.

“It does add up it’s kind of expensive, but in the end it’s worth it in terms of student learning,” she said.

Ms. Whitelaw said many schools adopt “solutions” that actually make noise distractions worse, such as adding tennis balls to the legs of desks to change a squeaking sound to a scratching sound when students move. The second sound may be quieter but more annoying.

“We know that noise is really distracting to kids’ attention, and affects kids’ stress levels,” Ms. Whitelaw said.

Repeated studies have found low-volume but chronic ambient noise raises cortisol, a chemical marker of stress, in both children and adults, but younger children are especially sensitive to it. Moreover, intermittent sounds, like a machine that turns on and off throughout the day, can have a stronger effect.

“When kids have high anxiety, and we are adding noise in the classroom, they are struggling to follow the teacher and they are getting exhausted by the end of the day,” Ms. Whitelaw said. “We know that’s a big factor in student performance.”

Noise and Attention

However, some studies are beginning to temper the thought that noise distraction is always bad.

In a study in the spring 2014 Journal of Applied Research in Memory and Cognition , which was discussed at the annual Society for Neuroscience conference in Washington in November, Swedish students were asked to learn texts in either an easy or difficult font, and in either a quiet classroom or one with low background speech—considered one of the most distracting types of sound. Students who had easy-to-read text had more difficulty remembering it when they had learned in a classroom with background speech, but students recalled more of the hard-to-read text when they were also coping with more ambient noise.

“A lot of it is the content of the noise” in comparison to what the student is doing, Ms. Whitelaw said. “If someone is having a conversation behind you, it’s more distracting if the teacher is lecturing, and you find it boring.”

Researchers suggested the students were more aware of the need to concentrate because the text seemed more difficult, and so were better able to “block out” the distractions.

Not every class can be outfitted with microphones or buffered with audio tiles, but Gary William Evans, a professor of human ecology at Cornell University, in Ithaca, N.Y., suggested in the Annual Review of Psychology that it is important for educators and students to be aware of how different noises will affect different types of students.

For example, in a study in the November issue of PLOS-One, researchers at the University of Southampton in England assigned five different tests of working memory—including word recall and recognition tasks, and a game in which students had to push a button or hold back in response to a cue—to 8- to 10-year-old students who had been rated by teachers as having low, normal, or high levels of attentiveness. The students performed the tasks in either a room with a quiet background or one with white noise of varying volumes, from 65 to 85 decibels.

The better that students were initially at paying attention, the worse they were affected by white noise at any level. By contrast, researchers found students with poor attention skills benefited from the additional noise, perhaps for the same reason sounds had helped students in the other survey remember text in a difficult font: The challenge may have sharpened their focus.

“Even if we have to say certain kids have to be in certain environments . the important thing is to know what the environment is: Make a measurement, just so you know what you are starting with,” Ms. Whitelaw said.

“A lot of things teachers think are good can be problems,” Ms. Whitelaw said. “We have teachers say, ‘I put music on to calm kids,’ but I’ve been in classrooms where they have music on pretty much throughout the day, even when there is lecturing, and it really contributes to the ambient noise. We’ve heard music is good, well, but let’s look at the sounds overall.”


Binaural Beats And Memory: Can This Crazy Music Make You Smarter?

It’s a popular perception among many people that listening to binaural beats has a special effect on the brain.

They think binaural beats can help you follow a diet or stop smoking.

Or they think these sounds can amp you up for a competition or calm you down, or even improve memory recall, focus and concentration.

Doesn’t listening to any type of relaxing music have a similar effect?

In this post, we’ll find out if listening to specific frequencies can have a better impact on your mental prowess than listening to Mozart for Pink Floyd!

Yours Free: A Private Course With Cheat Sheets For Becoming A Memory Master, Starting From Scratch.

>>> Click Here For This Special Free Offer.


Effects of Different Sound Waves

The different levels of sound waves can cause different effects on the brain and therefore the overall focus of an individual.

The way the brain works is by the billions of neurons that communicate to each other through electronic waves within it. As neurons fire, they can be affected by the external environment around them.

For example, if you have music on while you exercise, your body and mind will be prone to working out harder.

According to Dr. Jeffery Thompson, sound waves can affect the brain’s waves either positively or negatively. What’s more, the 4 types of brain waves – Alpha, Beta, Delta, and Theta – are prone to getting into sync with any music or sounds around you.

The human brain has a tendency to change its dominant EEG waves towards any external sounds around it. This can be positive and relaxing for some, but stressing for others.

Hypnotic Effects of Certain Sound Waves

Audio sensory can induce hypnosis in certain situations. This is known as binaural beat and it is an auditory illusion.

It can be achieved when two different sine waves with frequencies lower than 1500Hz and fewer than 40Hz between the two, are placed in each ear.

For example, if your right ear is listening to 1400Hz and your left ear is listening to 1370Hz, you can achieve this effect because your brain will automatically pick up a third tone – the binaural beat.

When the brain hears a binaural beat, it can cause an individual to feel hypnotized by the sound.

In comparison, of EEG’s brains that are listening to binaural beats and those that are experiencing meditation have nearly the exact same readings on the EEG charts.

White Noise for Maximizing Focus

White noise can provide a soothing and relaxing background noise, which can maximize your overall focus. There are different levels of ‘white’ noise which can include pink noise, white noise, and brown noise just to name a few.

When you are interested in improving your ability to concentrate, these different types of white noise can provide the stimulus your brain needs to focus, by delivering just the right amount of sound without the distraction of lyrics or intense musical beats.

The right kind of white noise can help relax your brain while still allowing you to hone your focus on the task in front of you.

If having background noise is something you enjoy and you want to increase your focus, try out the different degrees of white noise to find the one that will work best for you and your brain.

Sounds and focus directly correlate to your productivity. Finding the right balance of either silence, white noise, or stimulating music, can be crucial to your focus and therefore, your productivity.

Each and every one of us has a differently wired brain and sound will affect us differently, so it’s up to you to find what works best for your focus – silence, white noise, or your favorite songs.

Are you struggling with finding focus? Have you recently tried white noise? Let us know about your experience!

About The Author

This article is written by Sarah, the editor of Headphone Selection, which helps you choose the best headphones. She loves all sound technology and firmly believes in the power of positive music.

Looking for something?
Hey, I’m Lidiya

Thanks for stopping by. I’m Lidiya, a blogger, course creator and founder of Let’s Reach Success.

I help high vibe women create an abundant, value-driven business so they can live a fearless life and provide epic value.


2 Answers 2

Keep in mind the way they're defining "white noise" in the scientific american article you provided is different from what you link to on wikipedia. The SA definition is more in terms of ambient noise (e.g., traffic, low-level talking, a/c running, etc.) while white noise proper is a signal with a VERY specific acoustical pattern. It seems that the SA article is relating to deterioration in performance due to the stress caused by the increased attentional resources required to "tune-out" the ambient noise. If white noise proper completely eliminates all other ambient noise (without being too loud of course), this eliminates the allocation of these additional resources. Because white noise proper is essentially featureless, one will habituate to it unlike common ambient noise.

Carlson, Rama, Artchakov, & Linnankoski (1997) found a significant decrease in memory when exposed to music during a memory task and a significant increase in performance when exposed to white noise in comparison to a control which had only low level ambient noise. Though it was not the main purpose of the study, the authors conclude that music drew attention away and thus interfered while white noise likely drowned out the ambient noise without drawing attention and thus improved performance. Please keep in mind the sample of this study was on monkeys, but the processes are expected to be generalizable to humans.

Daee & Wilding (1977) found that the likelihood of forgetting during a free recall task is related to the level of noise to which one is exposed during rehearsal such that recall is best in a quiet environment and degrades at 75 and 85 dB. Though this study was not on concentration directly, these results can be seen to have applicable implications regarding attentional resources.

Along these same lines, Salame & Baddeley (1987) found significant differences in recall between unattended speech versus white noise such that unattended speech interferes with performance while no statistical difference was found in the white noise condition (in comparison to a quiet control). The authors conclude ". that noise does not interfere with short-term memory but that unattended speech does impair performance. "

The studies I cite above are related to memory recall tasks which, though involving similar processes to long-term concentration are not perfectly comparable. However, there is a pretty comprehensive literature showing the effects of noise exposure having negative effects on long-term tasks such as learning (e.g., Hygge, 1993, Lercher, Evans, & Meis, 2003). Additionally, Mathews & Canon, 1975 state "data [suggests] that arousal leads to a state of restricted attention or cue utilization in which attention is concentrated on salient features of the setting at the expense of its other aspects" which does not hinder attention to "central or salient events." This idea is related to the theory that noise facilitates functioning through the stimulation of processing such that increased arousal yields better performance until over-arousal occurs which then decreases performance (Hockey, 1983 from Staal, 2004). Stall (2004) also discusses the possibility of continuous v. intermittent noises having differential impact such that continuous may be beneficial while intermittent is harmful, though there is no current agreement in the literature (see pages 88-91).

Thus, the literature seems to support the following:

White noise will improve performance to the extent to which it masks noises that may cause over-arousal or attention shifts away from the task without causing over-arousal itself. Practically speaking, if you're in a quiet environment, white noise is unlikely to have a positive effect on your concentration. If you are in a somewhat noisy environment, white noise will likely have a positive effect. However, in a very noisy environment it will likely have either no or a negative effect.