journals.sagepub.com/home/pec Associated With Attention of ... · Associated With Attention of Students and Employees E. Tristań-Hernańdez Instituto de Investigacioń en ComunicaciońO´

Article

Influence of BackgroundNoise Produced in UniversityFacilities on the Brain WavesAssociated With Attentionof Students and Employees

E. Tristan-HernandezInstituto de Investigacion en Comunicacion Optica (IICO), Universidad

Autonoma de San Luis Potosı (UASLP), Mexico

I. Pavon-GarcıaGrupo de Investigacion en Instrumentacion y Acustica Aplicada (I2A2),

Escuela Tecnica Superior de Ingenieros Industriales (ETSII), Universidad

Politecnica de Madrid (UPM), Espana

I. Campos-CantonInstituto de Investigacion en Comunicacion Optica (IICO), Universidad

Autonoma de San Luis Potosı (UASLP), Mexico

L. J. Ontanon-GarcıaCoordinacion Academica Region Altiplano Oeste (CARAO),

Universidad Autonoma de San Luis Potosı (UASLP), Mexico

E. S. Kolosovas-MachucaCoordinacion para la Innovacion y la Aplicacion de la Ciencia y la

Tecnologıa (CIACyT), Universidad Autonoma de San Luis Potosı

(UASLP), Mexico

Abstract

As a consequence of noise exposure, lack of attention badly affects directly the academic and work

performance. The study of the brain and the waves that it produces is the most objective way to

evaluate this process. Attentional improvement is associated with increases of the amplitude in

both beta and theta bands. The objective of this work is to study the influence of background noise

produced inside university facilities on changes in the cerebral waves related to attention

processes (beta 13–30 Hz and theta 4–7 Hz). Volunteers were asked to perform a specific task

in which attention was involved. This task was performed in both silent and noisy conditions. To

evaluate the cerebral activity of volunteers during the development of the test, measurement of

spontaneous activity (electroencephalogram) was developed. The results show significant

Corresponding author:

E. Tristan-Hernandez, Instituto de Investigacion en Comunicacion Optica, Universidad Autonoma de San Luis Potosı, 78000

San Luis, Mexico.

Email: [email protected]

Perception

2017, 0(0) 1–13

! The Author(s) 2017

Reprints and permissions:

sagepub.co.uk/journalsPermissions.nav

DOI: 10.1177/0301006617700672

journals.sagepub.com/home/pec

https://uk.sagepub.com/en-gb/journals-permissions

https://doi.org/10.1177/0301006617700672

journals.sagepub.com/home/pec

decreases in both beta and theta frequency bands under background noise exposure. Since

attentional improvement is related to an increment on amplitude of both beta and theta bands,

it is suggested that decreases on amplitude of these frequency bands could directly be related to a

lack of attention caused by the exposure to background noise.

Keywords

electroencephalogram, background noise, university facilities, attention processes, beta and

theta waves

Introduction

Noise inside university facilities and its influence on the quality of life of university students,teachers, and workers is a topic that has received little attention. The university students,teachers, and workers spend a lot of time inside campuses with levels of noise higher than therecommended values (Balanay, Kearney, & Mannarino, 2016; Glass, Reim, & Singer, 1971;Tristan, Pavon, & Lopez, 2012; Tristan, Pavon, Lopez, & Kolosovas, 2016). In most cases,students themselves are the main source of noise (Tristan, Pavon, & Lopez, in press).

As is well known, high noise levels impact cognitive performance and particularly mayreduce the performance on tasks that require attention and memory (Salame & Baddeley,1987; Santiesteban, Sebastian, & Santalla, 1994; Surprenant, 1999). As a consequence, lack ofattention badly affects the academic (Hetu, Truchon, & Bilodeau, 1990; Lundquist,Holmberg, & Landstrom, 2000) and work performance (Errett, Bowden, Choiniere, &Wang, 2006; Persson, Rylander, Benton, & Leventhall, 1997),and may even increase therisk of accidents (Dıas, Cordeiro, & Goncalves, 2006).

Few studies have investigated the effects of noise on attention, but there is a consensus thatnoise of whatever kind and at whatever intensity level has significant repercussions onattention and memory (Baker & Holding, 1993; Barry, Clarke, & Johnstone, 2003; Barry,Johnstone, & Clarke, 2003; Cohen, Glass, & Singer, 1973; Kozou et al., 2005). Besides theeffects of noise in the attentional state, there are other factors that affect this process, forexample, visual factors (Chun & Wolfe, 2005), which may result in anxiety problems andmidperformance in the attentional state (Eysenck, 1988). However, the effects of noise are themost common in university facilities. Therefore, noise inside university facilities couldcertainly be considered as a risk factor for the health and safety of students andeducational workers.

To quantify and measure the effects discussed earlier, the scientific community relies on thebrain activity and the waves that it produces (i.e., beta and theta bands; Basar, Schurmann, &Sakowitz, 2001; Klimesch, 1999; Klimesch, Doppelmayr, Schimke, & Ripper, 1997;Lawrence, 2012). Brain wave activity typically is collected by measuring spontaneousactivity, also called electroencephalogram (EEG). This measurement is often used to assessthe attention state of test subject. Typically, event-related (ER) measures are a suitablemethodology to study cognitive processes (Basar, Rahn, Demiralp, & Schurmann, 1998;Teplan, 2002; Penny, Kiebel, Kilner, & Rugg, 2002). Nevertheless, usually amplitudes ofER components are much smaller than spontaneous EEG component, and hence, it isvery difficult to differentiate them from the EEG traces (Buzsaki & Draguhn, 2004;Teplan, 2002). Spontaneous EEG measurements are capable to describe the attentionalprocesses and some human behaviors due to the specific changes they may present.

2 Perception 0(0)

On the other hand, studies show the relationship between attentional processes and thechanges of specific cerebral waves. One of the main principles regarding the studies of brainwaves and attentional processes is that attentional improvement is associated with theincrease of the beta band (13–30Hz) and also the theta band (4–7Hz; Basar et al., 2001;Klimesch, 1999; Klimesch et al., 1997; Lawrence, 2012). Theta band have a big focaldistribution around the frontal-central and its amplitude does not exceed 100 mV (Basaret al., 2001). On the other hand, the ongoing EEG is an important tool for a betterunderstanding of cognitive functions. Spontaneous activity has a considerable influence onthe response immediately before an external stimulus (Basar et al., 2001; Klimesch, 1999;Klimesch et al., 1997). In the case of theta band, increases in spontaneous activity are relatedwith high creativity, memory, perception, mental tasks, and attention, especially duringencoding (Basar et al., 2001; Klimesch, 1999; Klimesch et al., 1997; Lawrence, 2012),reflecting sustained attention to the processing of new information (Klimesch, 2012).

The methodology used in most of studies has some similarities about sound conditions,mainly white noise, pink noise, and pure tones used as a sound stimulus. Silent and noisyconditions were also used to make comparisons (Baker & Holding, 1993; Barry, Clarke,et al., 2003; Barry, Johnstone, et al., 2003; Basar et al., 2001; Cohen et al., 1973;Klimesch, 1999; Klimesch et al., 1997; Lawrence, 2012).

The noise produced inside university facilities and its influence on the quality of life ofboth students and teachers is a topic that has received little attention (Tristan et al., 2016;Tristan et al., in press). In this way, more information is needed in order to have a betterunderstanding about the effects of noise over cognitive health.

Scope of Study

The main objective of this study is to investigate the effect of background noise producedinside university facilities on attentional processes. We seek a deeper understanding of therisk and consequences that noise may have on the psychological health of university membersthrough the study of cerebral behavior. The hypothesis is that if an individual is exposed tobackground noise during the performance of a specific task, the mean amplitude of beta andtheta bands activity will decrease.

Materials and Method

Participants

A total of 33 volunteers (students, teachers, and workers; 17 males and 16 females) agedbetween 19 and 34 years participated in the study. To be eligible to participate in the study,an evaluation of potential hearing loss of the participants was carried out according to ISO8253-1:2010: Acoustics—Audiometric test methods—Part 1: Pure-tone air and boneconduction threshold audiometry (International Organization for Standardization, 2010).None of the participants exceeded 20 dBHL in the frequency range 125Hz to 8 kHz.

Background Noise

The background noise used in the experiment was recorded inside university facilities duringnormal periods of work and study (from 8 a.m. to 6 p.m.). In total, six audio fragments wereused, recorded in the following environments: classrooms during an examination (CE),classrooms during a normal lesson, libraries, computer labs, hallways, and an adaptedstudy hall. The time duration of each sound fragment ranged from 1minute 30 seconds to

Tristan-Hernandez et al. 3

2minutes long. All fragments were mixed to construct a 10-min sound stimulus. The criterionused to choose the time laps recorded of each environment to perform the sound mix was touse the noisiest fragments, in other words, the fragments with the highest levels of noise.

Sound recordings were carried out using a handy recorder (Zoom H4n) which waspreviously calibrated in controlled acoustic conditions (anechoic chamber). The audio fileformat used was an uncompressed 16-bit stereo WAV file at a sample frequency of 44.1 kHz.Audio playback was carried out inside an audiometric chamber through headphones(Sennheiser CX 985), connected to a computer equipped with an external sound card(Mackie Onyx Satellite) and an audio editor software (Pro Tools D9). The playbackequipment was calibrated in an anechoic chamber using a head and torso simulator (Brueland Kjaer HATS—Type 4128D) analysis platform (Bruel and Kjaer—PULSE REFLEX).The same equipment mentioned above was used to develop the acoustic analysis of the soundstimulus and also to obtain both the total equivalent continuous noise level (LAeq,T) and theone-third octave spectrum of the sound environments.

Task

As the main goal of the present study was to investigate the negative effect of noise onattentional processes, the participants were asked to perform a task that requiredattention. The selected task consisted of the application of the Toulouse-Pieron test. Thistest is commonly used to evaluate attention capacity and perception. It consists of theidentification of three different figures, which are randomly distributed in 40 rows and 40columns (10 target figures per row). In brief, during 10minutes, participants had to identifythe largest number possible of targets (400) from a total of 1,600 figures. This test requireshigh demand of attention.

The test provides three indicators of effectiveness of the developed task: the total numberof successes (S), the number of errors (E), and the number of omissions (O). Once thisindicator has been obtained, it is possible to rate the performance (PR) using the followingequation:

PR ¼ S� ðEþ 0Þ ð1Þ

To know if there are significant changes in the scores of the tests, a repeated measurest-test was performed.

EEG Recordings

The experiment was carried out in an audiometric room in order to avoid sonorous andvisual distractions. The run time of the experiment with each volunteer was of 27minutesfollowing the timeline shown in Figure 1. The brain activity of the volunteers was recorded inboth silent (600 seconds) and noisy conditions (600 seconds), while they were performing theToulouse-Pieron test. In total, 1,200 seconds of recordings were performed taking one sampleevery 1 second (1,200 sample points).

The equipment used for the recording of the brain wave activity was a neurofeedbackequipment with five electrodes (Brainquiry PET EEG 2.0) and a software application in orderto collect the data (BioExplorer V.1.5). The following parameters were used to obtain thedata derived from the cerebral activity: band filters (theta, beta, alpha), resolution (1000ms),sensitivity (100mV), presentation of frequencies (0–45Hz), bandwidth of the graph inmedium frequency (3–30Hz), and finally, bandwidth of the total EEG. Moreover, in order

4 Perception 0(0)

to filtering artifacts such as the slow DC components, eye blink, and eyeball movements, ahigh-pass filter (2Hz, Butterworth, 6th order) and a low-pass filter (42Hz, FIR, 60 length)were used.

The electrodes were placed following the standard position referred to the international10-20 system (Klem, Luders, Jasper, & Elger, 1999; Niedermeyer & Lopes da Silva, 2004). Itis known that beta and theta bands are very evident in frontal lobe (Lawrence, 2012). On thisbasis, three of the five available active electrodes were placed on the frontal lobe on FpZ, Fp1,and Fp2; the reference electrode was placed on the right mastoid A1 and the negativeelectrode on the left mastoid A2.

On the other hand, a visual task had to be performed by the participants, and the alphawaves would typically disappear when the eyes are opened. The beta and theta bands are alsooften found to be related to attentional processes, and it is possible to study brain waveactivity in these bands when a person is awake and with his or her eyes open. Thus, in orderto identify a possible direct relationship between the exposure to noise and negative influenceson the attention, only changes in the beta (13–30Hz) and theta (4–7Hz) frequency bandswere studied. Statistical analyses on the data were performed using specialized statisticalsoftware (IBM SPSS Statistics V.19.0.0).

Statistical Design

First, in order to analyze if there were any changes in the performance of the task (Toulouse-Pieron test), a t-test of related differences were performed between both silent and noisyconditions.

On the other hand, the mean amplitude of beta and theta bands was measured, andstatistical descriptions were obtained. Furthermore, the normal distribution of the samplewas performed by means of the Kolmogorov–Smirnov (K-S) test. Beta D(33)¼ 0.212, p> .05,and theta D(33)¼ 0.181, p> .05 showed a normal distribution. Thus, a repeated-measureanalysis of variance (ANOVA) with Greenhouse–Geisser correction was performed inorder to determine if the differences in brain wave activity between both silent and noisyconditions were significant.

Results

Background Noise

The total equivalent continuous noise level (LAeq,T) for the complete sound stimulus was79.4 dBA. A summary of the results of each sound environment is presented in Table 1. Forseparate sound environments, the classroom during an examination registered 80.5 dBA,

Figure 1. Timeline of the experiment.


the library 79 dBA, the computer room 74.3 dBA, the classroom during a lesson 71.2 dBA,the adapted hallway registered 81.2 dBA, and finally, the adapted hall 82.1 dBA. Figure 2shows the temporal evolution of the sound stimulus, and Figure 3 shows the one-third octavespectrum of all environments recorded. A deeper acoustic characterization of the noiseenvironments used in the experiment has been reported in Tristan et al. (in press).

Task

To analyze if there were any changes in the performance on the Toulouse-Pieron test, the testwas applied both with and without background noise.

The results of the application of the test with the absence of background noise show thatthe minimum score registered was 134 points and the maximum was 305, with an average of234.3 points. On the other hand, when participants were exposed to background noise, theminimum score was 118 points, the maximum 361 points, and the average 246.2 points.

Table 1. Time and total equivalent continuous noise level of the sound stimulus used in the experiment.

Sound Environment CL LIB CR CE HW AH

Time (seconds) 90 90 90 90 120 120

Leq,T (dBA) 80.5 79.0 74.3 71.2 81.2 82.1

CL: classroom during a lesson; LIB: library; CR: computer room; CE: classroom during an exam; HW: adapted hallway;

AH: adapted hall.

Figure 2. Temporal evolution of the sound clip used in the experiments.

6 Perception 0(0)

The first assumption was that the background noise could generate negative changes onattention. In contrast, the results of the tests show that 55% of participants increase theirscore with an average of 11.9 points, when they were exposed to background noise. However,the repeated measures t-test indicates that there were no significant changes in the scores forthe test application, without background noise (M¼ 234.3, SD¼ 45.2) and with exposure tobackground noise (M¼ 246.2, SD¼ 52.2); t(32)¼ 1.723, p¼ .0945. Furthermore, a bigcorrelation (R2

¼ 0.8492) was observed between sound conditions. A general summary ofthe results is shown in Table 2.

EEG Recordings

Figure 4 shows the mean (averaged over time) of brain wave activity in both beta and thetabands for the 33 participants in both silent and noisy conditions. Table 3 shows a summary ofthe statistical descriptions. For the beta band in silent condition, the mean of the amplitude was

Figure 3. One-third octave spectrum of the sound environments recorded for the experiments.

Table 2. t-test of related differences of Toulouse-Pieron test between both silence and noisy conditions.

Mean of

differences D.S.

95% CI

t df p r R2Low High

Without noise vs.

With noise

11.9 48.811 �25.99 2.174 1.723 32 .0945 0.6762 0.8492


29.19mV, and when the participants were exposed to background noise, the mean amplitudewas at 21.67mV, resulting in a difference of �7.52mV. For the theta band in silence condition,the mean amplitude was 66.97mV, and in noisy condition, the mean amplitude was 54.22mV,resulting in a difference of �12.75mV. It is possible to observe subtle changes between the silentand noisy conditions. To determine if the differences in brain wave activity between bothconditions are significant, a statistical analysis was carried out. An ANOVA with aGreenhouse–Geisser correction was performed (Table 4). This test revealed significantchanges in both beta band, F(1,32)¼ 6.614, p¼ .015, and theta band, F(1,32)¼ 7.405, p¼ .010.

Furthermore, a decreasing tendency in both beta and theta bands was observed when theparticipants were exposed to background noise; 69.7% of the participants (N¼ 23) hadnegative changes in beta band and 75.8% of participants in the experiment (N¼ 25) alsohad negative changes in theta band. Figure 5 shows the EEG recording of 1 subject of the33 participants in the experiments, and Table 3 shows the statistical descriptions. Thistendency was also analyzed with repeated measures ANOVA with a Greenhouse–Geissercorrection (Table 5). The results show significant decreases in both beta band,F(1,22)¼ 15.206, p¼ .001, and theta band, F(1,24)¼ 24.084, p< .001.

Figure 4. Mean of the 33 participants and its changes in both beta and theta frequency bands.

Table 3. Summary of statistical descriptions of the EEG recordings of all the participants and participants

that experimented decreases in both beta and theta bands.

Min,mV Max,mV Mean,mV S.D.,mV

Mean of

diff., mV

All participants (N¼ 33)

� without noise 4.32 90.51 29.19 21.58 �7.52

� with noise 3.86 78.98 21.67 16.44

� without noise 20.58 167.89 66.97 33.8 �12.75

� with noise 9.15 107.05 54.22 26.04

Participants with decreases (N�¼ 23, N�¼ 25)

� without noise 6.53 90.51 33.24 22.09 �13.5

� with noise 3.86 61.34 19.73 14.29

� without noise 25.09 167.89 71.12 35.46 �22.23

� with noise 9.15 104.3 48.88 25.08

8 Perception 0(0)

Discussion

Sound Pressure Levels

According to R.D. 1367/2007 Royal Decree from Spain (Boletın Oficial del Estado [OfficialState Gazette], 2007) and ANSI/ASA S12.60-2010 standard (American National StandardsInstitute, 2010), the maximum level recommended for classrooms and study areas is 40 dBAand 60 dBA for surrounded areas. In the case of the background noise used for ourexperiments, we observed that these levels are exceeded almost the double for study areas(79.4 dBA) and almost 20 dBA above the recommended for surrounded areas. The noisiestenvironments are the areas that have been adapted as study areas: hallways and halls. Theseareas normally do not have the acoustic condition to develop study activities. Studentsnormally use it to socialize combined with study activities. The noise produced at theseplaces is another noise source that affects other areas of the campus such as libraries,classrooms, computer rooms, and so forth. Thus, the high levels of background noiseregistered at the university facilities could directly affect the university members. Theseareas could be considered as an unsuitable environment to develop study activities. It isvery important to develop strategies and measures in order to improve the life conditionsof university members.

Task Performance

The results obtained from the application of the Toulouse-Pieron test between both silent andnoisy conditions show that more than the half of the participants increase their score whenthey were exposed to background noise. Although this could suggest that background noiseimpacts positively on attention, the statistical tests show that the differences between bothsound conditions are not significant. Based on the results of the tests showed earlier, it isdifficult to estimate with this psychometric method whether background noise impacts

Table 4. Results of the ANOVA test of mean of the 33 participants in the experiments for both beta and

theta bands.

Source (N¼ 33)

Sum of

squares df

Mean

square F Sig.

Partial Eta

Squared

Beta Sphericity assumed .001 1 .001 6.614 0.015 .171

Greenhouse–Geisser .001 1.000 .001 6.614 0.015 .171

Huynh–Feldt .001 1.000 .001 6.614 0.015 .171

Lower bound .001 1.000 .001 6.614 0.015 .171

Error Sphericity assumed .005 32 .000

Greenhouse–Geisser .005 32.000 .000

Huynh–Feldt .005 32.000 .000

Lower bound .005 32.000 .000

Theta Sphericity assumed .003 1 .003 7.405 0.010 .188


Huynh–Feldt .003 1.000 .003 7.405 0.010 .188

Lower bound .003 1.000 .003 7.405 0.010 .188



Huynh–Feldt .012 32.000 .000

Lower bound .012 32.000 .000


positively on attention. Then, according to this, we consider that these results are notconclusive for the purposes of this research.

EEG Recordings

Since brain is the area where the cognitive processes are controlled, the recording of brainactivity through EEG studies show a clear idea of the effects that noise can produce oncognitive health of people.

After developing an extensive research on the methods used for the evaluation of cognitiveprocesses, we have carried out a methodology in accordance with the conditions of the study.This method is based on the combination of a task that demands attention and theelectrophysiological evaluation through electroencephalogram. This allows us to obtainobjective data.

The results of the acoustic evaluation reveal high levels of noise. As suggested earlier, theselevels of noise are high enough to cause negative effects directly on attention of the universitymembers. The hypothesis raised for this work is that ‘‘the exposure to background noisegenerates a negative influence on attention.’’ Consequently, decreases on beta and thetawaves could be observed.

Figure 5. EEG recording of one of the 33 subjects of the experiments. (a) Beta and (b) theta bands without

background noise (black line) and with exposure to noise (red line).

10 Perception 0(0)

So, a direct relationship between brain wave amplitude increases within the meanamplitude of beta and theta bands and the improvement of attention is often found inliterature (Basar et al., 2001; Klimesch, 1999; Klimesch et al., 1997; Lawrence, 2012).Thus, the collected data resulting from the analysis of the EEG results and its detailedstatistical analysis revealed that when volunteers were exposed to background noise, brainwave activity in both beta and theta bands dropped significantly during the attention taskperformance. This results suggest a direct relationship between the decreases of activity inbeta and theta bands and the decrease in attention arising from noise exposure.

Summary and Conclusions

In this work, we have presented a pilot study about the effects of background noise producedin university facilities on the brain waves associated with attention and memory amongstudents and employees.

First, in order to know the characteristics of the sound environments recorded in differentareas of the university campuses, acoustic analysis was performed in order to know the levelof noise at the soundscapes mentioned earlier. The obtained data were compared with thecurrent standards about noise at schools. The results reveal that the level of noise inuniversity areas destined to study activities are very noisy environments and unsuitable forstudy activities.

Furthermore, EEG recordings were performed to study the cerebral behavior ofvolunteers during the exposure to background noise while they were performing a taskthat required attention. As mentioned earlier, there are some other factors that may causenegative effects on attention. To control factors such as stray sounds and visual factors, the

Table 5. Results of the ANOVA test of the decrease tendency in mean amplitude of both beta and theta

bands.

Source (N¼ 23)

Sum of

squares df

Mean

square F Sig.

Partial Eta

squared

Beta Sphericity assumed .002 1 .002 15.206 0.001 .409


Huynh–Feldt .002 1.000 .002 15.206 0.001 .409

Lower bound .002 1.000 .002 15.206 0.001 .409



Huynh–Feldt .003 22.000 .000

Lower bound .003 22.000 .000

Source (N¼ 25)

Theta Sphericity Assumed .006 1 .006 24.084 0.000 .501


Huynh–Feldt .006 1.000 .006 24.084 0.000 .501

Lower bound .006 1.000 .006 24.084 0.000 .501

Error Sphericity Assumed .006 24 .000


Huynh–Feldt .006 24.000 .000

Lower bound .006 24.000 .000


experiments were developed in an environment free of this kind of distractors. With thismeasure, it was possible to focus attention on the sound stimulus and also on the task. Thus,with all this, the obtained results suggest that there exists a negative influence on attentionresulting from the exposure to background noise.

The method and results presented in this work contribute in a significant way for a betterunderstanding of how the noise generated in occupational environments affects the quality oflife of people. Furthermore, the method used in this work helps to develop an objectiveevaluation in order to evaluate the effects of noise on the attention and other psychologicalhealth upheavals. The findings of this study can be helpful for future researches.

Acknowledgments

We thank Bert De Coensel from the acoustics group at the Department of Information Technology of

Ghent University, Belgium, for their assistance in the review of this paper, and Andres Saldana from

Neuroscience Institute from Castilla y Leon (INCyL) of University of Salamanca, Spain, for their

assistance in data acquisition.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or

publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or

publication of this article: Edgar Tristan-Hernandez has been supported by The National Council for

Science and Technology (CONACyT), Mexico, for a postdoctoral position.

References

American National Standards Institute (ANSI). (2010). American National Standard Acoustical

Performance Criteria, Design Requirements, and Guidelines for Schools, Part 1: Permanent Schools(ANSI/ASA (2010), S12.60-2010). Washington, DC: Author.

Baker, M. A., & Holding, D. H. (1993). The effects of noise and speech on cognitive task performance.

The Journal of General Psychology, 120, 339–355.Balanay, J. A. G., Kearney, G. D., & Mannarino, A. J. (2016). Noise exposure assessment among

groundskeepers in a university setting: A pilot study. Journal of Occupational and Environmental

Hygiene, 13, 193–202.Barry, R. J., Clarke, A. R., & Johnstone, S. J. (2003). A review of electrophysiology in attention- deficit/

hyperactivity disorder: I. Qualitative and quantitative electroencephalography. ClinicalNeurophysiology, 114, 171–183.

Barry, R. J., Johnstone, S. J., & Clarke, A. R. (2003). A review of electrophysiology in attention-deficit/hyperactivity disorder: II. Event-related potentials. Clinical Neurophysiology, 114, 184–198.

Basar, E., Rahn, E., Demiralp, T., & Schurmann, M. (1998). Spontaneous EEG theta activity controls

frontal visual evoked potential amplitudes. Electroencephalography and Clinical Neurophysiology/Evoked Potentials Section, 108, 101–109.

Basar, E., Schurmann, M., & Sakowitz, O. (2001). The selectively distributed theta system: Functions.

International Journal of Psychophysiology, 39, 197–212.Buzsaki, G., & Draguhn, A. (2004). Neuronal oscillations in cortical networks. Science, 304, 1926–1929.Chun, M. M., & Wolfe, J. M. (2005). Visual attention. In E. B. Goldstein (Ed.), Blackwell handbook of

sensation and perception. Malden, MA: Blackwell Publishing Ltd. doi:10.1002/9780470753477.ch9

12 Perception 0(0)

Cohen, S., Glass, D., & Singer, J. (1973). Apartment noise, auditory discrimination, and reading ability

in children. Journal of Experimental Social Psychology, 9, 407–422.Dıas, A., Cordeiro, R., & Goncalves, C. G. (2006). Occupational noise exposure and work accidents.

Cad Saude Publica, 22, 2125–2130.

Errett, J., Bowden, E. E., Choiniere, M., & Wang, L. M. (2006). Effects of noise on productivity: Doesperformance decrease over time? (Architectural Engineering. Faculty Publications. Paper 13).Retrieved from http://digitalcommons.unl.edu/archengfacpub/13

Eysenck, M. W. (1988). Anxiety and attention. Anxiety Research, 1, 9–15.

Glass, D. C., Reim, B., & Singer, J. E. (1971). Behavioral consequences of adaptation to controllableand uncontrollable noise. Journal of Experimental Social Psychology, 7, 244–257.

Hetu, R., Truchon, C., & Bilodeau, S. (1990). Problems of noise in school settings: A review of

literature and the results of an exploratory study. Journal of Speech-Language Pathology andAudiology, 14, 31–39.

International Organization for Standardization (ISO). (2010). Audiometric test methods, Part 1: Pure-

tone air and bone conduction threshold audiometry (8253-1:2010). Geneva, Switzerland: Author.Klem, G. H., Luders, H. O., Jasper, H. H., & Elger, C. (1999). The ten-twenty electrode system of the

International Federation. Electroencephalography and Clinical Neurophysiology, 52, 3–6.

Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance:A review and analysis. Brain Research Reviews, 29, 169–195.

Klimesch, W. (2012). Alpha-band oscillations, attention, and controlled access to stored information.Trends in Cognitive Sciences, 16, 606–617. doi:10.1016/j.tics.2012.10.007

Klimesch, W., Doppelmayr, M., Schimke, H., & Ripper, B. (1997). Theta synchronization and alphadesynchronization in a memory task. Psychophysiol, 34, 169–176.

Kozou, H., Kujala, T., Shrytov, Y., Toppila, E., Starck, J., Alku, P., & Natanen, R. (2005). The effects

of different types of occupational noises on processing of speech and non-speech sounds: An ERPstudy. Hearing Research, 199, 31–39.

Lawrence, M. W. (2012). Synchronous neural oscillations and cognitive processes. Trends in Cognitive

Sciences, 7, 553–559.Lundquist, P., Holmberg, K., & Landstrom, U. (2000). Annoyance and effects on work from

environmental noise at school. Noise Health, 2, 39–46.

Niedermeyer, E., & Lopes da Silva, F. (2004). Electroencephalography: Basic principles, clinicalapplications, and related fields (pp. 140). Baltimore, MD: Lippincott Williams & Wilkins.

Official State Gazette (BOE). (2007) Royal decree 1367/2007 of October 19, which enacts the Spain’sState Law on Noise of 37/2003 in reference to acoustic zoning, quality objectives and acoustics

emissions (R.D. 1367/2007).Penny, W. D., Kiebel, S. J., Kilner, J. M., & Rugg, M. D. (2002). Event-related brain dynamics. Trends

in Neurosciences, 25, 387–389.

Persson, K., Rylander, R., Benton, S., & Leventhall, H. G. (1997). Effects on performance and workquality due to low frequency ventilation noise. Journal of Sound and Vibration, 205, 467–474.

Salame, P., & Baddeley, A. (1987). Noise, unattended speech and short-term memory. Applied

Ergonomics, 30, 1185–1194.Santiesteban, C., Sebastian, E. M., & Santalla, Z. (1994). Daily noise effects on memory. Psicothema, 6,

403–416.Surprenant, A. M. (1999). The effect of noise on memory for spoken syllables. International Journal of

Psychology, 34, 328–333.Teplan, M. (2002). Fundamentals of EEG measurement. Measurement Science Review, 2, 1–11.Tristan, E., Pavon, I., & Lopez, J. M. (2012). University sound environments. Proceedings of Euronoise,

Prague, Czech Republic, June 10–13, 257–262.Tristan, E., Pavon, I., & Lopez, J. M. (in press). Evaluation of psychoacoustic annoyance and

perception of noise annoyance inside university facilities. Int. J. Acoust. Vib.

Tristan, E., Pavon, I., Lopez, J. M., & Kolosovas, S. E. (2016). Evaluation of noise environmentsduring daily activities of university students. International Journal of Occupational Safety andErgonomics, 22, 274–278.


http://digitalcommons.unl.edu/archengfacpub/13

Documents

journals.sagepub.com/home/pec Associated With Attention of ... · Associated With Attention of Students and Employees E. Tristań-Hernańdez Instituto de Investigacioń en ComunicaciońO´