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  1. 1. The effect of partial sleep deprivation (24h) on gap detection thresholds and temporal ordering tasks Petri Nel Lezahn Prinsloo Supervisors: Dr. L. Pottas & Dr. M. Soer In partial fulfillment of the requirements for the degree B. Communication Pathology in the Department of Speech- Language Pathology and Audiology, Faculty of Humanities, University of Pretoria
  2. 2. 2 Abstract Objective: Temporal patterning abilities are connected with activity from the prefrontal cortex, which has been shown to be one of the primary areas affected by sleep deprivation. Therefore the main aim of this study was to determine the effect of partial sleep deprivation for a period of 24 hours on temporal patterning abilities in young adults with normal hearing and auditory processing abilities. Design: The duration pattern test was used in both the humming and labeling method of response to obtain results for temporal ordering tasks. The gaps-in-noise test was also employed and generated two different measurements, an approximation threshold and a percentage score. All measurements were obtained prior to sleep deprivation as well as after sleep deprivation had occurred. Study Sample: In the present study twenty healthy adult participants (9 females and 11 males, aged 22.65  0.72 years) were subjected to a preliminary screening protocol that included a pure tone audiometry test, immittance testing and Dichotic Digits Test. If participants met the selection criteria they were allowed to participate in the study. Results: The results obtained in the present study indicated a significant statistical difference for three out of the four measurements that were compared. No significant difference in results was found for the duration pattern test, labeling method of response. Conclusion: The findings of this study demonstrated that sleep deprivation affects temporal patterning abilities that are associated with the prefrontal cortex with the exception to complex tasks that elicit a compensatory response. Keywords: Temporal patterning, temporal resolution, sleep deprivation, prefrontal cortex, Duration pattern test, Gaps-in-Noise test
  3. 3. 3 Plagiarism Declaration DECLARATION Full name: Petri Nel Full name: Lezahn Prinsloo Student number: 11124432 Student number: 11135525 Degree: B. Communication Pathology Degree: B. Communication Pathology We declare that the research report is our own original work. Where secondary materials are used, this has carefully been acknowledged and referenced in accordance with university requirements. We understand what plagiarism is and are aware of the University of Pretoria's policy with this regard. ______________________ _____________________ SIGNATURE DATE ______________________ _____________________ SIGNATURE DATE UNIVERSITY OF PRETORIA FACULTY OF HUMANITIES DEPARTMENT OF SPEECH-LANGUAGE PATHOLOGY AND AUDIOLOGY
  4. 4. 4 Acknowledgements  Thank you to our supervisors, Dr. Pottas and Dr. Soer, for the guidance and motivation throughout the completion of our research project.  A very special thank you to all 20 participants that took part in our study. We really appreciate it and without them we would not have been able to complete our project.  Thank you to Sandile for the completion of the statistical analysis as well as the explanation and advice of the results.  Thank you to the Department of Communication Pathology for the provision of the equipment that was required in order to complete our data collection.
  5. 5. 5 Table of Contents List of Figures ............................................................................................................................................. 6 List of Tables............................................................................................................................................... 7 _____________________________________________________________________ ............................8 Introduction ............................................................................................................................................8 Methodology.........................................................................................................................................11 Aims of the study...............................................................................................................................11 Research design.................................................................................................................................11 Ethical considerations........................................................................................................................11 Participants .......................................................................................................................................12 Sampling method and sample size .................................................................................................12 Participant selection criteria ..........................................................................................................12 Materials and apparatus for preliminary screening protocol ..........................................................13 Procedures for screening protocol .................................................................................................14 Description of participants.............................................................................................................14 Materials and apparatus for gathering of data...................................................................................14 Audiometric equipment..................................................................................................................14 Gaps-in-Noise (GIN) .......................................................................................................................14 Duration Pattern Test (DPT)...........................................................................................................15 Procedures for data collection .......................................................................................................15 Data processing and analysis.................................................................................................................16 Results ..................................................................................................................................................17 Comparison of results of the BSL and post SD for DPT (humming method of response)......................17 Comparison of results of the BSL and post SD for DPT (labeling method of response) ........................18 Comparison of results of the BSL and post SD for GIN A.Th................................................................19 Comparison of results of the BSL and post SD for GIN percentage scores...........................................19 Discussion .............................................................................................................................................20 Conclusion.............................................................................................................................................24 Clinical implications...............................................................................................................................24 Recommendation..................................................................................................................................24 References ............................................................................................................................................25
  6. 6. 6 Appendices ................................................................................................................................................ 26 List of figures Figure 1: Comparison of the average of the DPT BSL results and post SD for the humming method of response (n=20)...............................................................................17 Figure 2: Comparison of the average of the DPT BSL results and post SD for the labeling method of response (n=20) .................................................................................18 Figure 3: The mean scores of the GIN approximation thresholds (A.Th): BSL and post SD results compared (n=20).............................................................................................19 Figure 4: The average of the GIN percentage scores: BSL and post SD results compared (n=20) ...............................................................................................................20
  7. 7. 7 List of Tables: Table 1: Screening apparatus used for participant selection...........................................13
  8. 8. 8 Abbreviations: CAP = Central auditory processing, CAPD = Central auditory processing disorder, DDT= Dichotic Digits Test, DPT = Duration Pattern Test, SD = Sleep deprivation, PFC = Prefrontal cortex, BSL = Baseline, GIN = Gaps-in-Noise, STDEV= Standard deviation, LPFC = Lateral prefrontal cortex, CRH= Compensatory Recruitment Hypothesis, A.Th = Approximation threshold, N= Norm _____________________________________________________________________ Introduction Sleep is a reversible state of consciousness that alternates with wakefulness and is characterized by an increased threshold to sensory input and decreased motor output. (Walker, 2009). These characteristic changes occur in the central and peripheral physiologic processes and conscious awareness diminishes (Walker, 2009). Sleep has important functions which include the homeostasis of energy systems, memory processing, thermoregulation and cognitive performance (Walker, 2009). In modern societies our lifestyles are associated with increased stress, and as a result, a decrease in the quantity and quality of sleep (Liberalesso, D'Andrea, Cordeiro, Zeigelboim, Marques, & Jurkiewicz, 2012). Several factors have been suggested that could possibly cause this reduction of sleep. These factors include adjustments in the environment and cultures such as increased environmental light, increased industrialization and more people doing shift work (Chokroverty, 2009). The unfortunate result of these factors is that sleep deprivation (SD) in adults have a prevalence of up to 20% (Hublin, Kaprio, Partinen, & Konskenvuo, 2001). Studies dating back as far as 1896 have demonstrated that insufficient sleep negatively affects cognitive performance in humans (Dinges, 2005). Studies showed an impairment of performance when sleep deprival occurred in humans proving sleep as a vital part of human functioning (Chokroverty, 2009). Sleep deprivation (SD) experimentation also demonstrates that sleep is essential for functioning, awareness, concentration and memory (Chokroverty, 2009). It is considered that adults require approximately 7.5 to 8 hours sleep continuously in a 24 hour period (Chokroverty, 2009). A decline in the duration of sleep that individuals obtain has been shown to negatively affect the immune, metabolic, and endocrine
  9. 9. 9 systems (Imeri & Opp, 2009). Partial SD occurs when an individual acquires less than seven hours of sleep in a 24 hour period (Dinges, 2005). SD and its effects on humans have been studied extensively; however, limited information is available on SD and its effect on central auditory processing (Liberalesso et al., 2012). ASHA (American Speech-Language Hearing Association) defines central auditory processing (CAP) as the way in which the central nervous system uses auditory information and stimuli (ASHA, 2005). CAP is cognitively responsible for language comprehension and for the following behavioral phenomena: localization and lateralization of sound; auditory pattern recognition; auditory discrimination; the temporal aspects of audition or sounds (including auditory masking, auditory resolution, integration, and ordering); as well as for the ability to compensate for auditory performance with degraded acoustic signals (Geffner & Ross-Swain, 2007). Chermak and Musiek (1997) state that speech reception and auditory processing of spoken language is a process much more intricate than simply the arrival of speech and sound at the eardrum (Mulder, Rogiers, & Hoen, 2010). Hearing involves a large number of mechanical and neurobiological operations and thus is not limited to the detection of an acoustic stimulus (Mulder et al., 2010). All these aspects of audition depend on the conveyance of neural information and impulses across synapses (ASHA, 2005). Auditory temporal resolution, a component of CAP, is a perceptual function connected with activity from the prefrontal cortex (PFC) (Liberalesso et al., 2012). The PFC is one of many brain regions that is first to be affected by SD (Zukerman, Babkoff, Fostick, & Ben-Artzi, 2005). Temporal resolution is the capability of the auditory system to react to fast alternations in the envelope of a sound over time and gap-detection models can be used to measure a primary aspect of this ability (Plack & Viemeister, 1993). This CAP task is essential for understanding speech in a quiet and noisy environment (Geffner & Ross-Swain, 2007). Tasks highly reliant on optimal PFC functioning will display a decrease in function, even with SD of a mild to moderate degree (24 hours) (Zukerman et al., 2005).
  10. 10. 10 Multiple tests are available to measure temporal resolution, in which the auditory systems' ability to resolve time, is assessed (Geffner & Ross-Swain, 2007). The Gaps- in-Noise (GIN) test, developed by Chermak and Musiek (2005), measures the detection of temporal modulation, duration discrimination and gap-duration discrimination. According to Geffner and Ross-Swain (2007), the GIN test provides better specificity than other temporal resolution measures as it has the smallest range and standard deviations. Another temporal processing skill is temporal ordering, which is the ability of an individual to process two or more auditory stimuli in order of the occurrence in time (Musiek & Chermak, 2007). Recognition of the temporal order of sounds is an essential perceptual ability for speech-understanding and relies on memory (Fogerty, Humes, & Kewley-Port, 2010). Information is stored in the working memory, but also needs to be categorized according to its order of occurrence (Katz, Medwetsky, Burkard, & Hood, 2009). The lateral prefrontal cortex (LPFC) is responsible for formulating and execution of plans and sequences of action (Katz et al., 2009). Therefore it is evident that since sequencing is a critical role in working memory, it is likely to be involved in the receptive aspects of ordering phonological information to develop its lexical representations and sequencing (Katz et al., 2009). Working memory tasks typically rely on brain function within the PFC, and the PFC has been identified as the brain region most vulnerable to SD (Walker, 2009). According to Walker (2009), studies that examined the brain function of tasks that rely on working memory following SD, have shown an increase and decrease in activation of the cerebral response (Walker, 2009). Therefore the effect of SD on the cerebral response to working memory demands remains unclear (Walker, 2009). It is speculated that the brain response to other working memory tasks possibly relies on the specific nature of the task demands and the specific sub-regions within the PFC underlying performance of those specific demands (Walker, 2009). Subsequently the compensatory recruitment hypothesis (CRH) was formulated that may explain this phenomenon. The CRH states that the brain possesses the ability to recruit additional cognitive resources during task performance following SD that aids in execution of tasks (Walker, 2009).
  11. 11. 11 Research has previously indicated that SD adversely affect processes associated with the PFC, thus we can hypothesize that SD could impair the functioning of central auditory processes that involve the PFC (Liberalesso, et al., 2012) and as a result it may influence the reliability of auditory assessment. SD and its effects on humans have been studied extensively; however, limited information is available on SD and its effect on CAP (Liberalesso et al., 2012). Therefore the primary aim of this study is to measure the effects of short periods of total SD (i.e. 24 hours) on temporal auditory processing. This will be achieved by using gap- detection thresholds and duration pattern tests to draw inferences on temporal resolution and -ordering functioning. Methodology Aims of the study The main aim of this study was to determine the effects of partial SD (i.e. 24 hours) on temporal processing. The sub aims were to determine the effects of partial SD on temporal ordering and temporal resolution skills, specifically using gap detection thresholds and duration pattern percentage scores to determine the effect of SD. Research design A descriptive comparative research design was selected and a quantitative approach was applied. This research design was employed due to the fact that two related samples, "before and after" results within the same individual, were determined and compared. The baseline (BSL) test results of adults with normal hearing were compared to test results that were obtained after SD had occurred. Ethical considerations As required for undergraduate studies, approval was obtained by the Departmental Research and Ethics Committee of the Department of Speech-Language Pathology and Audiology, University of Pretoria before any data collection commenced (See Appendix A). All participants signed an informed consent form prior to participation in testing
  12. 12. 12 procedures (See Appendix B). Confidentiality was maintained by allocating code numbers to each participant (SASHLA, 2010). Participants were given the option to withdraw from the study at any point in time (SASHLA, 2010). Participants Sampling method and sample size Random stratified and purposive sampling was used for the purpose of this study. This method was chosen as it increases the precision of the sample. (Ebrahim & Bowling, 2005). Participants were randomly selected from the University of Pretoria and surrounding communities with specific reference to their age. The termination of data collection occurred after 20 data sets were obtained. Participant selection criteria A sample of 20 participants, aged 18 to 30 years was recruited to participate in this research study. Participants had to present with normal hearing sensitivity (0 dB to 15 dB) as this is a prerequisite for auditory processing testing (AAA, 2010). Normal immittance results (Type A tympanogram; normal middle ear pressure -50 to +50 daPa, static compliance 0.3 to 1.75 ml and ear canal volume 0.4 to 1.0 ml and acoustic reflexes at 70 dB to 90 dB above threshold level were also considered as selection criteria as several studies (Katz et al., 2009) have demonstrated the possible negative impact that a peripheral hearing loss has on CAP test performance (AAA, 2010). In order to rule out the presence of auditory processing disorders (APD), the Dichotic Digits Test (DDT) was implemented. The DDT has been shown to be sensitive to cortical lesions that may affect temporal processing (Bellis, 2003). A previous study done by (Samelli & Schochat, 2008) also employed the DDT as a basic triage for auditory processing abilities of their participants. Participants scoring ≤ 80% with the DDT were excluded from the study as this is considered the norm for normal auditory processing abilities (Bellis, 2003). According to AAA (2010) an individual's cognitive status could influence their ability to complete complex behavioral measures of auditory functioning, thereby leading to inaccurate interpretation of results and may also render test results invalid. All participants were required to have competent cognitive status and to be proficient in the language of instructions (Afrikaans and English) given. Use of
  13. 13. 13 medication was prohibited, due to the fact that many drugs act as a stimulant that inhibits falling asleep (Walker, 2009) and may have an influence on the results. Stimulants such as caffeine and Modafinil maintain cognitive performance during sleep loss and thereby play a role in managing cognitive performance under a variety of conditions (Wesensten, 2012). Materials and apparatus for preliminary screening protocol Apparatus: Screening for participant selection Table 1 provides a summary of the materials and apparatus used during the preliminary screening protocol as well as the motivation for use. Scoring sheets for each corresponding test were utilized to record assessment results for each participant (See Appendix C). Table 1: Screening apparatus used for participant selection Assessment materials and apparatus Motivation for use Otoscopy (Welch-Allyn, Model 25270-MS) Visual inspection of ear canal, eardrum and bony structure of middle ear. Immittance (GSI Tympstar) (Calibration: January 2014) Assess middle ear functioning including compliance, ear canal volume and pressure. Assess the presence of stapedial reflexes. Hearing evaluation (GSI 61 Welch-Allyn audiometer equipped with Telephonic – 50 earphones) (Calibrated in January 2014) Assessed pure tone hearing thresholds to determine hearing sensitivity of individual. Dichotic Digit Test (Sansui CD210 CD player) Assessed central auditory processing (CAP) abilities namely; binaural integration and binaural separation (Bellis, 2003).
  14. 14. 14 Procedures for screening protocol All participants underwent a screening procedure prior to BSL testing in which they were required to complete a case history form, score above 80% for the DDT, had to have normal immittance and otoscopic findings, and normal pure tone thresholds (0 dB HL – 15 dB HL) across the frequency range i.e. 125 Hz to 8000 Hz. These tests were utilized to ensure that participants met the criteria which are required. Description of participants The cohort included 9 females (45 %) and 11 males (55 %), with a mean age of 22.65 (standard deviation, 0.72). Materials and apparatus for gathering of data Audiometric equipment Temporal processing tests was conducted using GSI 61 Welch-Allyn audiometer equipped with Telephonic – 50 earphones (Calibration: January 2014). A Sansui CD210 CD player was used to present test materials to participants, while seated in a sound proof booth Gaps-in-Noise (GIN) The GIN, developed by Frank Musiek and colleagues (Samelli & Schochat, 2008) was used to clinically measure participant’s temporal resolution abilities. Testing material consists of one practice list and four test lists, due to time constraints only the practice list, test one and test two item lists were utilized. A study showed that the equivalent forms reliability for the GIN test is high; therefore the choice of lists utilized does not affect the outcome of the results (De Lange & Hattingh, 2012). Another study done by Samelli et al. ((2008) demonstrated similar responses inter-lists and for both ears, confirming the above mentioned. Each item was presented monaurally at 50 dB HL above pure tone average (PTA). Ten practice items were presented to the participant to ensure that clarity was achieved. The GIN is composed of a series of computer- generated, equally distributed, broadband noise segments of six seconds in duration. Each six second segment of noise consists of zero to three silent intervals ranging from two to twenty ms embedded in six second segments of white noise. The position, number and duration of gaps per noise segment are randomized throughout the test
  15. 15. 15 (Samelli & Schochat, 2008). Scoring for the GIN is administered by means of calculating the GIN approximation threshold (GIN A.Th), followed by the GIN percentage score. Adult norms for the GIN A.Th is considered to be less than or equal to 8msec per segment of noise (Musiek & Chermak, 2007). The GIN percentage score cut off score for adults is 54% any score lower is perceived as abnormal (Musiek & Chermak, 2007). Duration Pattern Test (DPT) The DPT, also developed by (Musiek & Chermak, 2007), was used to assess temporal patterning abilities of participants. The DPT as described by Musiek and Chermak (2007) is composed of three pure tones per token; each tone is presented at 1000 Hz. These tones are either short (250 ms) or long (500 ms) in duration. An inter-tone interval of 300 ms is used for testing. The DPT consists of six randomizations (LLS, LSL, LSS, SLS, SLL and SSL) and uses a 6 second inter-pattern interval. The DPT was used with both methods of response, ‘humming’ and ‘labeling’. Participants were instructed to; firstly, label the sounds they heard by categorizing the sound as short or long, thereafter they were instructed to hum what was heard. A list of 20 items was presented monaurally for each method of response. One item consisted of three tones. Participants had to correctly label or hum all three tones for the item to be recorded as correct. The DPT was presented 50 dB HL above participant’s PTA. The percentage scored correctly by participants was established for each of the variables. Procedures for data collection CAP assessment protocol CAP was assessed with the use of the GIN and the DPT at two different periods of time, BSL and after 24 hours post SD. The BSL CAP tests were conducted immediately after the initial hearing evaluation on the subjects who adhered to the selection criteria. The BSL results were obtained on participants in a normal (rested) state and the second test was performed after participants had no sleep continuously for 24 hours. A researcher remained with participants throughout the night to ensure participants did not fall asleep and to ensure that the validity of results was maintained. Activities such as watching television or playing computer games were the preferred choice of activity during the SD
  16. 16. 16 period. All participants were prohibited from smoking; consuming any medication, stimulants, caffeine, or alcohol for the 24 hours between the BSL and 24 hours SD test sessions. Data processing and analysis Data processing The data collected was entered in master charts by the two primary researchers and analyzed quantitatively using statistical methods. Thereafter the data were refined to a single Microsoft Excel (2007) sheet, replacing the raw data with the corresponding assigned coded values to the outcomes of each test. The DPT consists of two ear specific lists of 25 items, each used correspondingly. This score indicates the number of items out of 25 which the subject indicated correctly. The following formula was employed to calculate percentage score per ear: The GIN has two measures of analysis, the approximation threshold (A.Th) and the overall percentage correct. The A.Th is the shortest gap duration for which there were at least four of six correct (67%) identifications (Shinn, Chermak, & Musiek, 2009).The number of gaps correctly identified represents the overall percentage score (Shinn, Chermak, & Musiek, 2009). These percentages do not refer to the approximation thresholds (A.Th) but to the gaps perceived (Samelli & Schochat, 2008). Results were presented as means for both gap detection thresholds and percentage scores. The approximation threshold (A.Th) and percentages of correct responses are unrelated and independent variables (Samelli & Schochat, 2008). Data analysis The Statistical Software Package SPSS 15.0 was employed to analyze the data and Microsoft Word and Excel were used to generate graphs, tables etc.
  17. 17. 17 Figure 1: Comparison of the average of the DPT BSL results and post SD for the humming method of response (n=20) The Kolmogorov-Smirnov test was used to determine if data was distributed normally. Most of the variables relevant to this study, were not distributed normally, thus nonparametric procedures was the more reliable method to use. Comparing two related samples, according to Corder and Foreman (2009), the appropriate nonparametric test is the Wilcoxon Signed Ranks test (Corder & Foreman, 2009). The level of significance adopted for this study was <0.05 which is represented as the p- value. If the p-value is < 0.05, it indicates that there is a statistically significant difference at a 5% level of significance (Williams, Sweeney, & Anderson, 2009). Results The results of this study are discussed according to the set sub aims. Comparison of results of the BSL and post SD for DPT (humming method of response) In order to determine the effect of SD on temporal ordering, the BSL results of the DPT were compared to the post SD results. In Figure 1 it is that evident that there was a decrease in the average scores (85.55%, STDEV=16.88) after SD had occurred in comparison to the BSL (95.3%, STDEV= 6.66) results The cut off score of 73% as set out by Bellis (2003) indicates that both scores obtained fall within normal limits (Bellis, 2003). The average DPT (humming) 95.3 85.55 0 20 40 60 80 100 PercentageScores Participants DPT (Humming) BSL Post SD
  18. 18. 18 percentage scores following 24 hours of SD (24hSD) were significantly lower than those observed during the BSL condition without SD. A p-value of <0.001 was calculated with the Wilcoxon Signed-Rank test when results of the BSL and post SD were compared. Comparison of results of the BSL and post SD for DPT (labeling method of response) The BSL percentage scores of the DPT were compared to the post SD scores for the labeling method of response. Figure 2 indicates the results obtain by the participants for DPT labeling method of response. Figure 2 projects a slight visual difference between the results observed for BSL (86.63%, STDEV= 16.97) and the post SD (82.65%, STDEV=17.09) for DPT labeling method of response. Bellis (2003) set out a cut off score for DPT (labeling) of 73% for both ears (Bellis, 2003). Both results obtained fall within normal limits. No significant difference was obtained for this method of response in the DPT with a p-value of <0.131, indicating that SD did not adversely affect the DPT in the case of labeling method of response. 86.63 82.65 0 10 20 30 40 50 60 70 80 90 100 PercentageScores Participants DPT (Labelling) BSL PostSD Figure 2: Comparison of the average scores for the DPT BSL results and post SD for the labeling method of response (n=20)
  19. 19. 19 Comparison of results of the BSL and post SD for GIN A.Th The first score calculated for the GIN was the approximation threshold (A.Th). The A.Th is the shortest gap duration for which there were at least four of six correct (67%) identifications. BSL results were compared to the results obtained post SD (Figure 3). Figure 3 provides a clear representation of the threshold shift that occurred between the BSL (A.Th=4.9, STDEV=0.83) and post SD (A.Th=5.68, STDEV= 0.91). The normative value for A.Th is ≤ 8 ms, therefore both results obtained are within normal limits (Musiek & Chermak, 2007). The Wilcoxon Signed-Rank test was used to compare the results obtained in the two different conditions. The results indicate a statistically significant difference with a p-value <0.006, demonstrating that SD had a significant effect on GIN A.Th when BSL and post SD results were compared. Comparison of results of the BSL and post SD for GIN percentage scores The second score calculated for the GIN was a percentage score indicating the number of gaps correctly identified. BSL results were compared to the results obtained post SD. 4.9 5.67 4.4 4.6 4.8 5 5.2 5.4 5.6 5.8 BSL Post SD GINA.Th BSL vs Post SD Figure 3: The mean scores of the GIN approximation thresholds (A.Th): BSL and post SD results compared (n=20)
  20. 20. 20 Figure 4: The average of the GIN percentage scores: BSL and post SD results compared (n=20) In Figure 4 it is evident that overall percent scores obtained by participants after 24hSD (62.88%, STDEV=8.30) declined compared to results obtained during BSL (70.93%, STDEV= 6.18) testing. The cut-off score for percent correct is ≤54% for adults, therefore both scores obtained fall within normal limits (Musiek & Chermak, 2007). The p-value of <0.000 as calculated by the Wilcoxon Signed-Rank indicated a significant statistical difference between BSL results and post SD results. Discussion The overall aim of this study was to measure the impact of SD on temporal auditory processing in a group of healthy adults, specifically the impact on temporal resolution and temporal ordering skills. This was achieved by comparing results in the GIN and DPT in a BSL (rested) condition as opposed to after 24 hours of SD. A significant decline in performance was observed in three out of the four (75%) measurements that were compared. In a study done by Liberalesso et al. (2012), two temporal processing tests were employed, the Random Gap Detection Test (RGDT) and Staggered Spondaic Word Test (SSWT), and were compared prior to SD and after 24hSD. The 70.93 62.88 58.00 60.00 62.00 64.00 66.00 68.00 70.00 72.00 GINPercentageScores Participants BSL Post SD
  21. 21. 21 study revealed that both the RGDT and SSWT worsens after SD had occurred, which substantiates the hypothesis that perceptual functions that are connected with PFC activity are affected by SD (Liberalesso et al., 2012). Studies done by Harrison and Horne (2000) have revealed that during wakefulness the PFC is the most active (i.e. highest metabolic rate of all cortical regions) and that the PFC is one of the first brain regions to suffer as a result from SD (Harrison & Horne, 2000). Therefore, the current study was based on the premise that functions connected to PFC activity are primarily affected by SD. This theory predicts that SD will influence complex tasks that require higher cortical-related skills. Temporal ordering: DPT Firstly, the present study revealed a decrease in the ability of participants to correctly sequence items presented during the DPT for the humming method of response, this was determined by the mean scores of performance before and after SD. However, only a slight decline in performance was observed for the DPT labeling method of response (Fig. 2) and the results did not reveal a significant difference before and after SD. Due to the increased complexity that accompanies the labeling method of response a greater decline with the labeling method of response compared to the humming method of response would be expected. To strengthen the argument, a study showed that young South African adults performed better in the humming method of response (94.83% left, 95.92% right), than in the labeling method of response (87.42% left, 86.08% right) (Veenstra & Buys, 2013). The inference of this being that humming is a simpler task than labeling, therefore the impact of SD would be greater on the labeling method response. This discrepancy in these methods of response after SD had occurred for the DPT can be explained by a study that demonstrated that an increase in task difficulty facilitates the cerebral compensatory response in the presence of SD (Drummond, Brown, Salamat, & Gillin, 2004). A verbal-learning task showed a significant increase in cerebral responses in both the PFC and the parietal lobes following SD (Drummond et al., 2004). Additionally, there have been multiple findings showing that SD has a more deleterious effect on performance of lengthy and boring tasks than on those that are
  22. 22. 22 shorter and more interesting (Gosselin, De Koninck, Cambel, & Kenneth, 2005). However Harrison and Horne (2000) demonstrated that tasks depending on the prefrontal lobes were still greatly affected by SD even when tasks are interesting and short (Harrison & Horne, 2000). The above mentioned thus can explain that due to the increased difficulty that arises in the labeling method of response, a cerebral compensatory was most likely elicited and therefore participants did not show a significant decline in performance after 24hSD. This finding is further supported by another study that indicated that tasks that rely on working memory (i.e temporal ordering) may elicit a compensatory response in the presence of SD, depending on the degree of attention that the task at hand demands (Dinges, 2005). Studies using positron-emission tomography (PET) and functional magnetic resonance imaging (fMRI) revealed that certain regions of the brain changed in response to SD (Dinges, 2005). PET studies illustrated an overall decrease in glucose metabolism throughout cortical and sub-cortical regions during SD (Dinges, 2005). However an increase in impairment of cognitive tasks after SD, showed that glucose uptake decreased more specifically in the PFC, thalamus and posterior parietal association cortices (Dinges, 2005). fMRI studies confirm that after 24hSD, attention- demanding tasks increased thalamic activation and this is thought to demonstrate a neuroanatomical correlate of increased "mental energy" that occurs during a low state of arousal (Dinges, 2005). The study demonstrated that verbal working memory after SD resulted in decreased temporal lobe activation and increased parietal lobe activation (Dinges, 2005). This increase is associated with the preservation of working memory function (Dinges, 2005). The above mentioned therefore suggests a possible neurophysiological mechanism that uses posterior cortical systems to elicit a compensatory response in the presence of SD and can thus explain the results obtained in this study. Temporal resolution: GIN The outcome of this research study revealed a significant difference in thresholds obtained pre- and post SD during the GIN test. Results indicated an incline in the GIN
  23. 23. 23 A.Th post SD, hence an increase in the length of the shortest gap duration perceived for which there were at least four out of six correct (67%) identifications. These results are confirmed by a recent study on the effects of SD on CAP that indicated that the time period that was needed to recognize the gap of silence between matching sound stimuli in the Random Gap Detection Test (RGDT) post SD, revealed a negative impact of SD on temporal resolution ability (Liberalesso et al., 2012). According to a study done by Babkof et al. (2005), 24 hours of SD reduces auditory temporal resolution by 28% or more and affects higher level cognitive functions such as language comprehension and auditory processing (Kerkhof & Van Dongen, 2010). With regard to the GIN percentage scores the results of the current study indicated a decline in the participants’ ability to accurately identify the number of gaps after SD. These results can be explained by research indicating that the auditory function of temporal resolution (including gap -detection) rely on the functioning of the PFC, which is affected by SD (Kerkhof & Van Dongen, 2010). Kerkhof and Van Dongen proposed a study that explains the ‘sleep- based neuropsychological perspective’ that was first explained by Harrison and Horne in 1983, which serves as an alternative to the ‘classical arousal hypothesis, in a detailed manner. This research study suggest that the various parts of the brain are affected differently by SD and that the area in the brain (PFC) involved in auditory processing or more specifically, temporal resolution, is directly affected by SD (Kerkhof & Van Dongen, 2010). The PFC, which is one of the first areas in the brain to be affected by SD, is most active during wakefulness and plays a critical role in the perception of speech (Babkoff, Zukerman, Fostick, & Ben-Artzi, 2005). As SD has an influence on the functioning of the frontal lobe and consequently the PFC, it can also affect the expression and perception of speech and language (Liberalesso, et al., 2012). As the current study indicated that participants performed worse in temporal resolution tasks post SD it might consequently affect their speech perception abilities, due to the fact that speech perception is highly reliant on temporal resolution.
  24. 24. 24 Conclusion In conclusion, the results presented in this study demonstrated that partial sleep deprivation for a period of 24 hours is sufficient to significantly affect temporal processing abilities, i.e. temporal ordering (humming method of response) and temporal resolution, in healthy young adults. The decline in performance of participants confirms that SD negatively affects the processes associated with the PFC. The impairment of these abilities following sleep deprivation may be due the effects of SD on neurobiological functions that are essential for the processing of auditory information which include memory, attention, concentration, reaction time and stimulus perception. Additionally, no significant decline in performance was observed for the DPT (labeling) due to the elicitation of the cerebral compensatory response in tasks that had a higher attention-demand and increased task difficulty. Clinical implications The results of this study revealed the significant effect that SD may have on CAP, specifically temporal processing abilities, which are essential for speech perception. Any CAP testing can thus be influenced by SD and therefore questions regarding sleeping habits and/or sleeping disorders should be considered in the case history prior to CAP testing. This will increase accuracy and reliability of results obtained from CAP tests consequently enabling audiologists to make a more accurate diagnosis of central auditory processing disorders (CAPD). Recommendation The recommendations for future research studies include the increase in sample size that will enable researchers to make more reliable interpretations of the findings. The present study was done according to a five day inter-test time frame due to time constraints which might reduce the accuracy of the findings; therefore it is suggested that the inter-test interval time should be increased to yield more accurate results.
  25. 25. 25 References AAA. (2010). Diagnosis, treatment and management of children and adults with Central Auditory Processing Disorder. American Academy of Audiology. ASHA. (2005). (Central) Auditory Processing Disorders. Working Group on Auditory Processing Disorders , 2. Babkoff, H., Zukerman, G., Fostick, L., & Ben-Artzi, E. (2005). Effect of the diural rhythm and 24 h of sleep deprivation on dichotic temporal order judgment. European Sleep Research Society , 8. Bellis, T. J. (2003). Assessment and Management of Cetral Processing disorder in the educational setting, 2nd Edition. Canada: Delmar. Chokroverty, S. (2009). Sleep Disorders Medicine: Basic science , technical considerations and clinical aspects. Philadelphia: Saunders Elsevier. Corder, G. W., & Foreman, D. I. (2009). A step-by-step approach. Hoboken :New Jersey: John Wiley & Sons, Inc. De Lange, N., & Hattingh, T. (2012). Temporal resolution: Gin (Gaps-in-Noise test) Performance in normal hearing South African Adults. Pretoria: University of Pretoria. Dinges, J. S. (2005). Neorocognitive consequences of sleep deprivation. Seminars in neurology volume 25 , number 1 , 117-129. Drummond, S. P., Brown, G. G., Salamat, J. S., & Gillin, C. J. (2004). Increasing Task Difficulty Facilitates the Cerebral Compensatory Response to Total sleep deprivation. SLEEP, Vol. 27, No. 3 , 448-450. Ebrahim, S., & Bowling, A. (2005). Handbook of Health Research Methods. In Investigation, research and analysis (p. 197). Berkshire, England: McGraw-Hill International. Fogerty, D., Humes, L. E., & Kewley-Port, D. (2010). Auditory temporal-order processing of vowel sequences by young and elderly listeners. The journal of the acoustical society of America . Geffner, D., & Ross-Swain, D. (2007). Auditory Processing Disorders. Assessment, Management, and Treatment. San Diego: Plural Publishing. Gosselin, A., De Koninck, J., Cambel, & K. B. (2005). Total sleep deprivation and novelty processing: implications for frontal lobe functioning. Clinical Neurophysiology , 211-222. Harrison, Y., & Horne, J. A. (2000). The impact of sleep deprivation on descion making : A review. Journal of Experimental Psychology: Applied , Vol 6, No. 3 236-249. Hublin, C., Kaprio, J., Partinen, M., & Konskenvuo, M. (2001). Insufficient sleep: A population based study in adults. Sleep, Volume 4 , 392-400.
  26. 26. 26 Imeri, L., & Opp, M. R. (2009). How (and why) the immune system makes us sleep. Nat Rev Neuroscience , 199-210. Katz, J., Medwetsky, L., Burkard, R., & Hood, L. (2009). Handbook of clinical audiology (6th ed.). Philadelphia: Lippincott Williams & Wilkins. Kerkhof, G. A., & Van Dongen, H. P. (2010). Progress in brain research. Human sleep and Cognition. Part 1: Basic research , 112. Liberalesso, P. B., D'Andrea, K. F., Cordeiro, M. L., Zeigelboim, B. S., Marques, J. M., & Jurkiewicz, A. L. (2012). Effects of sleep deprivation on central auditory processing. Liberalesso et al. BMC Neuroscience , 13:83. Mulder, H. E., Rogiers, M., & Hoen, M. (2010). Auditory Processing Disorders: Identification, diagnostic, aetiology and management. Speech and hearing review , 239-266. Musiek, F. E., & Chermak, G. D. (2007). Handbook of (Central) Auditory Processing Disorder. Auditory Neuroscience and diagnosis. Volume 1. San Diego: Plural Publishing. Plack, c., & Viemeister, N. (1993). Suppression and the dynamic range of hearing . J Acoust Soc Am , 93: 976-982. Ratcliff, R., & Van Dogen, H. P. (2009). Sleep deprivation affects multiple distinct cognitive processes. Psychon Bull rev , 742-751. Samelli, A., & Schochat, E. (2008). the gaps-in -noise test : Gap detection thresholds in normal hearing young adults. International Journal of Audiology , pp. 47, 238-245. SASHLA. (2010). South African Speech-Hearing-Language Association :Code of ethics. Ethics and Standars Committee: Published by SASHLA Office. Shinn, J. B., Chermak, G. D., & Musiek, F. E. (2009). GIN (Gpas-in-Noise) Performance in the pediatric population. Journal of the American Academy of Audiology , 232. Vanderstoep, S. W., & Johnson, D. D. (2009). Research methods for everyday life. In Blending quantitative and qualitative appraoches (p. 3). San Francisco: Jossey-Bass. Veenstra, J., & Buys, A. (2013). Temporal Patterning skills of young South African adults with nomral hearing and auditory processing. University of Pretoria , 26. Walker, R. S. (2009). The neuroscience of sleep. London: Academic Press. Wesensten, N. J. (2012). Sleep Deprivation, Stimulant Medications, and Cognitions. New York: Cambridge University Press. Williams, T. A., Sweeney, D. J., & Anderson, D. R. (2009). Contemporary Bussiness Statistics with Custom Slections. University of Pretoria Edition: Cengage Learning EMEA.
  27. 27. 27 Zerouali, Y., Jemel, B., & Godbouta, R. (2009). The effects of early and late night partial sleep deprivation on automatic and selective attention: An ERP study. Elsevier , 95. Zukerman, G., Babkoff, H., Fostick, L., & Ben-Artzi, E. (2005). Effect of the diurnal rhythm and 24 h of sleep deprivation on. journal of sleep research , 7-15.
  28. 28. 28 Appendix A: Ethical clearance
  29. 29. 29 Appendix B: Informed consent Dear Participant, REQUEST FOR PARTICIPATION IN A RESEARCH STUDY As final year students in B.Communication Pathology (Audiology) at the University of Pretoria, it is required that we conduct a research study and submit a research report in partial fulfillment of our degree. In our study we will examine the effects of partial sleep deprivation (lack of sleep for 24 hours) on temporal auditory processing (the ability to perceive time related changes in acoustic stimuli) and speech recognition in noise. Due to the lack of information available on this topic, the results obtained in the study may be valuable for future research studies Participation in this study will require that you visit the Department of Communication Pathology at the University of Pretoria. Upon arrival you will be asked to complete a short background history pertaining to your hearing. A set of tests will be administered to ensure that hearing and processing of sound is normal. You will then be required to return to the department on a different date. On this day we require you to remain awake continuously for 24 hours. Thereafter we will repeat the set on tests administered to measure the effects on hearing and processing of sound. Participation in this study is completely voluntary and participants may withdraw from the study at any time without any negative consequences. Participation in this study does not pose any risk for participations. All identifying information of participants will be kept confidential. The data will be kept for 15 years for archiving and research purposes before being destroyed. The data obtained will be available to our supervisors, Dr. L Pottas and Dr. M Soer, as well as the Head of Department of Communication Pathology, Prof. B Vinck. All the relevant results will be complied in a research report, which will be available at the University of Pretoria. Participants may also request to view the results obtained. By signing the informed consent, you agree to the following:  Having good sleeping behaviors  Not using any of the following stimulants on the day of testing:  Coffee and tea  Coca cola or any other soft drink containing caffeine, including Redbull and Monster energy drinks  Alcohol  Smoking  Not using any medication
  30. 30. 30 If you require any additional information, you are welcome to contact us at 0849228064 or 0842932855. Your participation will be greatly appreciated. Yours Sincerely, Petri Nel (Student) Lezahn Prinsloo (Student) Dr. L Pottas (Supervisor) Dr. M Soer (Supervisor) Prof. B Vinck HEAD OF DEPARTMENT OF COMMUNICATION PATHOLOGY
  31. 31. 31 Appendix C: Scoring Sheets
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