Relevant Thesis-Based Degree Programs
Affiliations to Research Centres, Institutes & Clusters
Complete these steps before you reach out to a faculty member!
- Familiarize yourself with program requirements. You want to learn as much as possible from the information available to you before you reach out to a faculty member. Be sure to visit the graduate degree program listing and program-specific websites.
- Check whether the program requires you to seek commitment from a supervisor prior to submitting an application. For some programs this is an essential step while others match successful applicants with faculty members within the first year of study. This is either indicated in the program profile under "Admission Information & Requirements" - "Prepare Application" - "Supervision" or on the program website.
- Identify specific faculty members who are conducting research in your specific area of interest.
- Establish that your research interests align with the faculty member’s research interests.
- Read up on the faculty members in the program and the research being conducted in the department.
- Familiarize yourself with their work, read their recent publications and past theses/dissertations that they supervised. Be certain that their research is indeed what you are hoping to study.
- Compose an error-free and grammatically correct email addressed to your specifically targeted faculty member, and remember to use their correct titles.
- Do not send non-specific, mass emails to everyone in the department hoping for a match.
- Address the faculty members by name. Your contact should be genuine rather than generic.
- Include a brief outline of your academic background, why you are interested in working with the faculty member, and what experience you could bring to the department. The supervision enquiry form guides you with targeted questions. Ensure to craft compelling answers to these questions.
- Highlight your achievements and why you are a top student. Faculty members receive dozens of requests from prospective students and you may have less than 30 seconds to pique someone’s interest.
- Demonstrate that you are familiar with their research:
- Convey the specific ways you are a good fit for the program.
- Convey the specific ways the program/lab/faculty member is a good fit for the research you are interested in/already conducting.
- Be enthusiastic, but don’t overdo it.
G+PS regularly provides virtual sessions that focus on admission requirements and procedures and tips how to improve your application.
ADVICE AND INSIGHTS FROM UBC FACULTY ON REACHING OUT TO SUPERVISORS
These videos contain some general advice from faculty across UBC on finding and reaching out to a potential thesis supervisor.
Graduate Student Supervision
Doctoral Student Supervision
Dissertations completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest dissertations.
Reading success in a second language (L2) is crucial for billions of people worldwide, but it is well known that it remains difficult for L2 learners to automatize the L2 processing in general. I investigated how long-term reading experience in a first language (L1) might change the neural L1 orthographic processing, and if these results can be generalized to L2 orthographic processing. I recruited adult monolingual English readers and adult Mandarin readers with late-language learning of English. By contrasting single-letters with pseudoletter visual stimuli (a pseudoletter effect) in L1, the reaction time data showed that reading experience makes letter processing faster than in pseudoletter processing. The electroencephalogram data showed that the L1 pseudoletter effect was manifested in a left-dominant oscillatory activity and network dynamics. The electroencephalogram data also showed that the L1 pseudoletter effect was robust, regardless of the level of attention paid; letters elicited more of left-lateralized neural connectivity desynchronization than did pseudoletters. Additionally, the data from L2 showed that the magnitude of the L2 pseudoletter effect in the N170 in the left hemisphere was correlated with L2 proficiency. Taken together, I concluded that with reading experience, the brain has automatized orthographic processing, which is evidenced by being (1) more specific by shifting the processing demands to different neural regions within visual processing networks—left dominant for well experienced orthographies, (2) being more obligatory, at least, at the single-letter level, and (3) faster by completing the process of differentiating letters from pseudoletters at fairly early stages of visual processing. Further, I concluded that some of the above changes appear to be ready throughout adulthood; orthographic development appears to be free from the fossilization or critical period hypotheses.
Master's Student Supervision
Theses completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest theses.
The aim of this project was to provide normative behavioural threshold data for brief-tone and chirp stimuli, two stimuli that are used in auditory brainstem response (ABR) testing. I collected thresholds from 20 typical-hearing adults using fixed-frequency Bekesy audiometry with a 1-dB step-size. The test stimuli, 5-cycle exact Blackman-gated brief-tones and CE-chirps, were collected via both air-conduction (ER-3A inserts) and bone-conduction (B-71 oscillator) at a presentation rate of 10/s at every octave from 250 - 4000 Hz, with 6000 Hz also tested for air-conduction. I also collected brief-tones at 1000 Hz at a rate of 20/s for both air- and bone-conduction in the interest of comparing the effect of stimulation rate on threshold. Data analysis showed air-conduction chirp thresholds were a statistically significant 1.80 dB higher on average compared to brief-tone thresholds, and bone-conduction chirp thresholds were similarly significantly elevated by 2.56 dB. I found that air-conduction brief-tone thresholds did not significantly differ from the norms published by the BCEHP (Hatton, Van Maanen, & Stapells, 2022; Small & Stapells, 2017). Air conduction normative threshold results for brief-tones and chirps were significantly greater by 3.93-5.57 dB for frequencies 500 and 1000 Hz compared to previous literature (Fedke & Richter, 2007; Gøtsche-Rasmussen, Poulsen, & Elberling, 2012), although these results are generally below our a-priori definition for clinical significance of ≤5 dB. BC results were significantly lower by 7.21 – 19.67 dB compared to previous literature (Small & Stapells, 2003) for 500 through 2000 Hz, all of which fall above our definition of clinical significance. A closer look at my data revealed variable participant response patterns to the Bekesy audiometry procedure. Thus, there is a caveat to the results collected in this study, and further research is needed to explore the reliability of intra-participant response patterns in comparison to other automated and manual behavioural audiometric tests.
Language processing differs in native language speakers and language learners, and making progress encapsulating these differences in brain responses is difficult due to the complexity of the brain. In particular, late second language learners are posited to differ in learning in comparison to native or bilingual speakers, for instance in phonological knowledge. Deep Learning Neural Networks (DLNN) offers the opportunity to capture nuances of electroencephalographic (EEG) data that could be less perceivable using ERP methods. Using DLNN analyses of EEG data could be another tool sensitive for identifying and categorizing the data. The present study used a DLNN to categorize EEG data from L1 (native) and LL2 (late 2nd language learners) English speakers while they listened to English phonemes. A subset of participants from both L1 and LL2 groups was used to train the DLNN and then another different subset of participants was used to test the DLNN performance on categorizing single-trial EEG of L1 participants from EEG of LL2 participants. Overall the results showed that the trained DLNNs were reasonably accurate at categorizing novel speakers with 73% ± 8% accuracy. This may be evidence that there are general processing differences between native speakers and learners of a language.
Analysis of cortical auditory evoked potentials (CAEPs) can provide valuable insight into how sounds are processed differently based on subject and stimulus parameters. Having a thorough understanding of these norms is necessary to use techniques for detecting a variety of neurological impairments, for evaluating hearing thresholds in patients who are unreliable or difficult to assess behaviourally, and for monitoring brain plasticity. Specifically, areas of central processing that can be investigated using electrophysiological methods include the ability to detect sounds, discriminate between sounds, and the ability to recognize and notice similarities or differences in sound patterns. There is also potential for CAEPs to be used to monitor speech processing. Possible applications of monitoring speech using CAEPs include validating hearing aids, assessing neural plasticity in hearing aid and cochlear implant users over time, and determining the efficacy of auditory training in improving speech perception. In order to effectively record and analyze CAEPs for any purpose, it is essential that clinicians have a thorough understanding of how stimulus factors such as intensity, duration, frequency, and presentation rate affect the positive and negative components of CAEPs. Furthermore, clinicians must be well versed in their understanding of CAEP maturational changes, as components show changes in latency, amplitude, and variability over the life span. On account of CAEPs being generated from higher level cortical areas, they are also highly mediated by subject state and attention. As such, it is critical that these factors be taken into consideration when comparing data across participants, and when comparing individual data with norms. Through the process of conducting a scoping review, this thesis outlines morphological trends of CAEPs as a function of both stimulus and subject parameters, highlights the interdependency of such variables, and identifies avenues for further research. Furthermore, data has been compiled into a freely available resource which clinicians may contribute to as additional research is conducted.
Cortical auditory evoked potentials (CAEPs) are believed to reflect the neural discrimination and encoding of sound. These responses include obligatory evoked potentials including the P1-N1-P2 complex. The P1-N1-P2 response that occurs at the beginning of the stimulus presentation is called the onset response, while the P1-N1-P2 response that occurs at the re-introduction of sound, such as after a silent interval (gap) in noise stimulus, is called the auditory change complex (ACC). Though the onset and the ACC responses are evoked by the same auditory stimulus, the matter of whether they are mediated by the same physiological mechanisms is met with inconsistency in the cortical auditory evoked response literature. The current trend is to refer to the responses as different events, indicating a possible belief that the source generators are also different. This retrospective study of 35 participants’ datasets tested the null hypothesis that both the onset and ACC responses are generated from the same neural location. Dipole source modelling was conducted on existing CAEP gap-detection data to determine each response’s source generators. Results showed dipoles for the ACC were significantly located more posteriorly (0.4±1 mm) than dipoles for onset P1-N1-P2 response, thus rejecting the null hypothesis. These unexpected results provide evidence that the transient onset and ACC responses are likely undergoing differing underlying neural processes in response to acoustic changes in the environment. These findings allow researchers to more confidently refer to both the onset and ACC responses as different events, thereby diminishing confusion and increasing accuracy of future discussions about and clinical applications with CAEPs.
Purpose: Conventional audiometry, used to detect elevated hearing thresholds, is insensitive to cochlear pathologies involving cochlear synapse degeneration in the absence of hair cell or nerve fiber loss. Patients with this pathology—known as cochlear synaptopathy (CS)— report symptoms such as tinnitus and speech in noise difficulty despite clinically normal hearing thresholds. Current methods for identifying CS in animals require immunohistochemistry, however this invasive technique cannot be translated to clinical diagnostics. The present study aims to evaluate the diagnostic potential of the cochlear microphonic (CM) for noise-induced CS via electrocochleography. Design: The CM in response to 95 dB nHL broadband clicks was recorded via tympanic membrane electrocochleography. 18 music students (n = 32; mean age = 21.7) with normal hearing thresholds (≤ 25 dB, HL 250-8000 Hz) and 19 normal hearing controls (n = 35; mean age = 22.5) were recruited for the study. Lifetime noise exposure was obtained using the NESI. A repeated-measures ANOVA was used to analyze the effects of music background and rater on CM/CAP amplitude, CM duration, and CM area under the curve. Correlation tests were performed between NESI scores and liberal or conservative CM power calculations. Inter-rater reliability was tested using a multiple regression design. Inter-class correlation tests were performed on liberal and conservative CM/CAP amplitude and CM duration values. Results: There were no significant group differences on any of the electrocochleography measures. Lifetime noise exposure scores were not significantly different between groups. Conclusion: The present study found no evidence that CM/CAP amplitude, CM duration, or CM area under the curve are associated with noise exposure. Results suggest 1) no effect of CS on the cochlear microphonic, 2) electrocochleography is insensitive to CS, or 3) noise exposure is too low to detect CS. It is possible the effects of noise exposure may be observed in individuals with greater lifetime noise exposure than those recruited for the study. Use of tympanic membrane electrocochleography to assess CS in humans remains inconclusive. Additional research is needed to develop a clinical diagnostic protocol for early cochlear damage that precedes hair cell loss.
Cortical auditory evoked potentials (CAEPs) are neural responses that occur in response to changes in sound, which can be recorded from electrodes placed on the scalp. The N1-P2 response can be reliably used to determine a person’s frequency-specific hearing thresholds. This objective method for hearing assessment is used clinically in situations where the patient is unable or unwilling to provide reliable behavioural responses. Currently, the gold standard method of interpreting CAEP results is dependent upon the visual judgment of the clinician. A high level of noise in the recordings may obscure a small N1-P2 response. Established criteria for an acceptable residual noise (RN) level does not currently exist. Such criteria could be used as a tool to assist in the interpretation of CAEPs, making judgments more reliable among clinicians. The goal of the present study was to estimate a noise criterion based on recorded and simulated CAEP averages with various different levels of RN.CAEP results at threshold and sub-threshold intensities were recorded for 12 normal hearing adults at 500 Hz and 2000 Hz. Each waveform was presented a total of five times, with each average including a different number of sweeps. Simulated CAEPs were generated (N=37), with averages including a variety of different RN levels. The waveforms were presented to three expert raters, who judged each waveform independently as having an N1-P2 response present or absent. RN criterion, maximal noise floor allowable for judging a response as truly absent, was determined when raters performed at 95% sensitivity of detecting a true response. The recommended criteria for the maximum noise floor level were 0.111 μV (relative to the pre-stimulus interval) or 0.145 μV (relative to the post-stimulus interval). Simulated data exhibited a better face validity than the recorded CAEPs. Further studies may lead to the implementation of new guidelines surrounding RN criteria in CAEP recording procedures. Such guidelines may provide more validity and reliability in clinical practice.
Objectives: The cochlear microphonic (CM) is a bioelectric potential detectable through early latency auditory brainstem responses (ABR). It has been described as large in amplitude and long in duration in auditory neuropathy spectrum disorder (ANSD), a complex form of hearing loss. ANSD is identified through a combination of diagnostics, including but not limited to present otoacoustic emissions (OAEs) and/or a robust CM, and absent/abnormal ABR. Based on previous literature, this study hypothesized that CMs would differ significantly between infants with ANSD and normal-hearing infant data from well-baby, and neonatal intensive care unit (NICU) populations; it further hypothesized that CM/ABR wave V (CM/V) amplitude ratios would not differ significantly across ANSD groups presenting with and without OAEs. Design: Retrospective analysis was performed on click-ABR recordings from 16 infants with ANSD (24 ears; mean 3.5 months, corrected) for comparison to published normative data. ANSD was identified by the presence of OAEs (OAE+) and absent/abnormal ABR, and by CM presence with abnormal/absent ABR and support from later behavioral results for infants with absent OAEs (OAE-). Waves were analyzed by comparing condensation and rarefaction polarities to highlight the CM. Proposed CM/V ratio values for ANSD identification were also explored. Results: Mean CM durations were significantly longer in combined ANSD ears (4.197 ± 1.154ms) than normally-hearing well-baby (0.73 ± 0.3ms) and NICU (0.82 ± 0.51ms) infants. CM amplitudes were significantly larger in ANSD (0.322 ± 0.173µV) than well-baby (0.24 ± 0.09µV), but not NICU (0.26 ± 0.13µV) infants. OAE+ and OAE- ANSD ears did not differ significantly in CM duration or amplitude but did differ significantly in mean CM/V ratios (6.602 ± 2.987, 2.040 ± 1.112, respectively). Ratios correctly identified ANSD in 16 of 19 ANSD ears with a wave V. Conclusions: Significant group differences in CM duration suggest that this measure could be useful for identification of ANSD in infants. CM amplitude was less definitive, with confounds between datasets. The CM/V ratios failed to correctly categorize all OAE- infants for which the measure would be most applicable. Results should be viewed with caution given the retrospective nature and limited sample size of the analysis.
Objectives: In cases of auditory neuropathy spectrum disorder (ANSD), clinicians may defer amplification until reliable behavioural thresholds can be obtained, as auditory brainstem response (ABR) assessment often overestimates thresholds. Limited research has investigated the correlation between ABR-estimated and behavioural thresholds. This study aims to retrospectively quantify the management practices found in ANSD patients identified through the British Columbia Early Hearing Program (BCEHP). The relationship between ABR and hearing aid (HA) fitting thresholds will be investigated for evidence to support using ABR thresholds to inform early intervention. Methods: BCEHP patient data was obtained for the 28 children diagnosed with ANSD between 2008 and 2015. Information such as clinical demographics and the use of hearing technology was extracted. The age of diagnosis and intervention was reviewed for 1-3-6 month benchmark compliance. ABR and HA fitting threshold data was collected, and comparative analysis was performed. Results: Analysis revealed that the average age of ANSD diagnosis was 7.8 months corrected (range: 1.5 – 69 months), and the average time between diagnosis and amplification was 10 months (SD: 15 months). Comparative analysis revealed that while delaying amplification is appropriate for the majority of ANSD patients, fitting to ABR-estimated thresholds may be suitable in a small subset. Conclusions: HA fitting for ANSD infants is often delayed beyond 6 months of age. Study results suggest that in some cases, ABR thresholds may be sufficient to generate prescriptive targets for amplification. Further research is needed to corroborate these findings and provide support for early intervention based on ABR-thresholds.
Gap-detection testing is a measure of temporal resolution, a component of auditory processing that is sometimes affected in Central Auditory Processing Disorder (CAPD). Using behavioural gap-detection tasks as part of a CAPD battery can be confounded by attention, in that it is difficult to distinguish whether poor performance is a result of attention deficits or central auditory processing deficits. Researchers have assessed the utility of cortical auditory evoked potentials (CAEPs) as an objective measure of gap-detection thresholds. The present study aimed to compare CAEPs during a passive and active gap-detection task to assess the effects of attention on electrophysiological gap-detection testing. The results showed no significant differences in gap-detection thresholds obtained behaviourally, obtained electrophysiologically during the passive task, and obtained behaviourally or electrophysiologically during the active task. N1-P2 amplitudes were found to be significantly larger in the active gap-detection task compared to the passive task. In conditions where a 0 ms duration or subthreshold duration gap was presented, an N2b waveform was evoked. The N2b is an endogenous event-related potential (ERP) that is usually evoked when a prepotent response must be withheld, such as during the no-go trials of a go/no-go task. Because the gap-detection task could be considered as a go/no-go paradigm, the N2b was likely evoked due to the unfulfilled expectation of a gap occurring with predictable timing and high probability. The goal of experiment 2 was to investigate the occurrence of this endogenously-evoked no-go N2b as previous literature has focused primarily on the N2b evoked by exogenous stimuli. The results found that all participants had an N2b wave to no-gap and subthreshold gap conditions. There were no significant correlations between N2b-P3a amplitudes and behavioural thresholds or between N2b-P3a amplitudes or N2b latencies and reaction time or reaction time standard deviation. There was a significant correlation between P3a amplitudes and ex-Gaussian reaction time standard deviation. No significant differences were found between N2b amplitudes for correct rejections or misses. Overall, this study demonstrated that the no-go N2b can be evoked by an endogenous signal in the form of the omission of an expected gap in noise.
Cortical auditory evoked potentials (CAEPs) are currently being investigated as a tool for validation in hearing aid fittings. There is some conflicting evidence regarding the usefulness of CAEPs in this capacity. CAEPs are influenced by stimulus parameters and hearing aids can change these parameters in an unpredictable manner. The purpose of this study was to investigate the effect of rise time after hearing aid processing on the CAEP of 23 normal hearing participants. Two different duration stimuli (60 ms and 120 ms) were processed by three different hearing aids and the output of each hearing aid was recorded. The stimulus parameters were measured for each condition and the stimuli were presented to each participant through an insert earphone. Two blocks of stimuli were used (1) Raw (varied SNR and intensity) and (2) Equalized/Filtered (equalized SNR and intensity). The electroencephalography (EEG) was recorded and the P1-N1-P2 amplitudes and latencies were measured for each condition. A three-factor ANOVA was conducted to observe the effects of (1) rise time, (2) duration, and (3) SNR. A main effect of rise time was observed on the N1-P2 amplitude. This result indicated that hearing aid processing can increase the rise time enough to elicit a decrease in the N1-P2 amplitude. No effects were observed on amplitudes or latencies of the N1-P2 with the alternative stimulus parameters (SNR and duration). Prior to using CAEPs clinically for validation of hearing aid fittings, normative standards should be established. This ensures that differences in the N1-P2 amplitudes are due specifically to audibility and not to the altered stimulus parameter (i.e., after hearing aid processing). Further research should also be conducted on individuals with hearing loss to see if the effects observed in this study would be present with this population. In addition, comparisons of behavioural and CAEP methods of validation would be helpful in determining the validity and reliability of using these methods clinically.
Temporal resolution is the ability of the auditory system to detect small changes over time and is an important component for the detection and decoding of speech by the central auditory nervous system. Temporal resolution is most often measured by asking a person to detect small gaps between sounds, known as behavioural gap-detection tests. However, certain populations may be unable or unwilling to respond reliably due to perceptual or cognitive deficits, or in medico-legal compensation cases. There are limitations to behavioural gap-detection measures because they cannot separate cognitive from perceptual deficits. The present study utilized electrophysiological gap-detection measures as a means of objectively estimating behavioural gap-detection thresholds. Cortical auditory evoked potentials (CAEPs) are neural responses to changes in sound, duration, and frequency that can be measured from the scalp. The specific aim of this study was to collect adult normative data for CAEP gap-detection thresholds to examine if CAEPs could accurately estimate behavioural gap-detection thresholds. Gap-evoked CAEPs could be recorded in participants who were awake and passively listening and could estimate temporal resolution without the need for a participant’s cooperation or attention. The results showed that there was a significant N1-P2 response to gaps at ≥ 4 ms, with 85% of participants having a response to a 10 ms gap. Additionally, the electrophysiological mean gap-detection threshold was within 1 ms of behavioral mean gap-detection threshold. This demonstrated that gap-evoked CAEPs can accurately estimate behavioural gap-detection thresholds in a normal hearing adult population.
Previous audiovisual Stroop studies used spoken colour-words mainly as ignored distractors when performing the visual Stroop task. Previous matching Stroop studies in the visual domain provided opposing views regarding whether interference effects resulted from conflicting semantic representations or conflicting responses. This study’s main objective was to explore how a written word distractor affects audiovisual matching of a spoken colour-word and font colour. I presented colour-words written in congruent or incongruent font colours simultaneously with spoken colour-words. Participants pressed buttons to indicate whether the spoken word and font colour were “same” or “different”, while ignoring written word meaning. I recorded response times and accuracy to measure interference and facilitation effects between experimental and control conditions. I hypothesised that incongruent written words (e.g., red) would interfere with “same” responses (e.g., font colour = blue, spoken word = /blue/) but facilitate “different” responses (e.g., font colour = green, spoken word = /blue/); and that congruent written words (e.g., red) would facilitate “same” responses (e.g., font colour = red, spoken word = /red/) but interfere with “different” responses (e.g., font colour = red, spoken word = /blue/, or font colour = blue, spoken word = /red/). The results showed large interference effects but no facilitation effects on audiovisual judgements. While incongruent written words interfered with “same” responses, congruent written words interfered with “different” responses. The largest interference effect occurred when the written word was incongruent with both task-relevant dimensions, while smaller effects occurred when the written word was congruent with either task-relevant dimension. Consistent with previous Stroop findings, my audiovisual matching task showed that in the case of cross-modal colour judgements, written word meaning predominantly interferes with but does not facilitate performance. The pattern of results showed that a conflict between the outcome of the relevant matching task and the outcomes of two mistakenly performed matching tasks involving the written word produced interference effects, rather than a conflict among the semantic representations activated by the three stimulus dimensions.
Infant hearing-health programs have a goal of identifying infants with a permanent hearing loss by the age of three months and treating these infants by the age of six months. However, deficits in hearing thresholds are not the only deficits that exist in the auditory system. The ability of an infant's auditory system to resolve rapid changes in acoustic signals (i.e., temporal resolution) and integrate acoustic information over time (i.e., temporal integration) is important for typical language development. Because behavioural responses are unreliable for diagnostic purposes before the age of six months, electrophysiological measures of temporal resolution and integration could be beneficial. The main objective of my thesis was to validate in adults if 80-Hz auditory steady-state responses (ASSRs, an objective electrophysiological measure) can be used to assess temporal resolution and integration. Physiological temporal resolutions of adults were estimated from cortical auditory evoked potentials (CAEPs) and ASSR resets evoked by gaps (1.5625, 3.125, 6.25, 12.5, and 25 ms) within 40-Hz and 80-Hz amplitude-modulated white-noise bursts. Physiological gap-detection thresholds for CAEPs (8 ± 6 ms, averaged across conditions), 40-Hz ASSR resets (6 ± 5 ms), and 80-Hz ASSR resets (5 ± 4 ms) were comparable to behavioural gap-detection thresholds (5 ± 2 ms). However, 40- and 80-Hz ASSRs maximally reset to half-cycle gap durations (i.e. 12.5 and 6.25 ms respectively), thus ASSR resets might not be truly measuring gap-detection thresholds. Conflicting results from CAEPs and ASSR resets to gaps provides evidence that CAEPs respond preferentially to all gaps down to threshold; whereas, ASSRs preferentially reset to gaps that violate their modulation periodicity. Physiological integration times (117 ± 48 ms, averaged across conditions), as measured from the rise time of the ASSR resets, were comparable to behavioural measurements of temporal integration (132 ± 83 ms). However, more research is required to determine if physiological and behavioural integration times are correlated or are coincidentally similar. These results indicate that CAEPs are accurate measures of temporal resolution. However, further research is required to determine the utility of ASSR resets in assessing temporal resolution and integration.