Browsing by Author "Shoushtarian, Mehrnaz"
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- ItemAssessing hearing by measuring heartbeat: The effect of sound level(PLoS One, 2019-03) Shoushtarian, Mehrnaz; Weder, Stefan; Innes-Brown, Hamish; McKay, ColetteFunctional near-infrared spectroscopy (fNIRS) is a non-invasive brain imaging technique that measures changes in oxygenated and de-oxygenated hemoglobin concentration and can provide a measure of brain activity. In addition to neural activity, fNIRS signals contain components that can be used to extract physiological information such as cardiac measures. Previous studies have shown changes in cardiac activity in response to different sounds. This study investigated whether cardiac responses collected using fNIRS differ for different loudness of sounds. fNIRS data were collected from 28 normal hearing participants. Cardiac response measures evoked by broadband, amplitude-modulated sounds were extracted for four sound intensities ranging from near-threshold to comfortably loud levels (15, 40, 65 and 90 dB Sound Pressure Level (SPL)). Following onset of the noise stimulus, heart rate initially decreased for sounds of 15 and 40 dB SPL, reaching a significantly lower rate at 15 dB SPL. For sounds at 65 and 90 dB SPL, increases in heart rate were seen. To quantify the timing of significant changes, inter-beat intervals were assessed. For sounds at 40 dB SPL, an immediate significant change in the first two inter-beat intervals following sound onset was found. At other levels, the most significant change appeared later (beats 3 to 5 following sound onset). In conclusion, changes in heart rate were associated with the level of sound with a clear difference in response to near-threshold sounds compared to comfortably loud sounds. These findings may be used alone or in conjunction with other measures such as fNIRS brain activity for evaluation of hearing ability.
- ItemCortical fNIRS Responses Can Be Better Explained by Loudness Percept than Sound Intensity(Wolters Kluwer Health, Inc, 2020-01) Weder, Stefan; Shoushtarian, Mehrnaz; Olivares, Virginia; Zhou, Xin; Innes-Brown, Hamish; McKay, ColetteOBJECTIVES: Functional near-infrared spectroscopy (fNIRS) is a brain imaging technique particularly suitable for hearing studies. However, the nature of fNIRS responses to auditory stimuli presented at different stimulus intensities is not well understood. In this study, we investigated whether fNIRS response amplitude was better predicted by stimulus properties (intensity) or individually perceived attributes (loudness). DESIGN: Twenty-two young adults were included in this experimental study. Four different stimulus intensities of a broadband noise were used as stimuli. First, loudness estimates for each stimulus intensity were measured for each participant. Then, the 4 stimulation intensities were presented in counterbalanced order while recording hemoglobin saturation changes from cortical auditory brain areas. The fNIRS response was analyzed in a general linear model design, using 3 different regressors: a non-modulated, an intensity-modulated, and a loudness-modulated regressor. RESULTS: Higher intensity stimuli resulted in higher amplitude fNIRS responses. The relationship between stimulus intensity and fNIRS response amplitude was better explained using a regressor based on individually estimated loudness estimates compared with a regressor modulated by stimulus intensity alone. CONCLUSIONS: Brain activation in response to different stimulus intensities is more reliant upon individual loudness sensation than physical stimulus properties. Therefore, in measurements using different auditory stimulus intensities or subjective hearing parameters, loudness estimates should be examined when interpreting results.
- ItemCortical Processing Related to Intensity of a Modulated Noise Stimulus—a Functional Near-Infrared Study(SpringerLink, 2018-04) Weder, Stefan; Zhou, Xin; Shoushtarian, Mehrnaz; Innes-Brown, Hamis; McKay, ColetteSound intensity is a key feature of auditory signals. A profound understanding of cortical processing of this feature is therefore highly desirable. This study investigates whether cortical functional near-infrared spectroscopy (fNIRS) signals reflect sound intensity changes and where on the brain cortex maximal intensity-dependent activations are located. The fNIRS technique is particularly suitable for this kind of hearing study, as it runs silently. Twenty-three normal hearing subjects were included and actively participated in a counterbalanced block design task. Four intensity levels of a modulated noise stimulus with long-term spectrum and modulation characteristics similar to speech were applied, evenly spaced from 15 to 90 dB SPL. Signals from auditory processing cortical fields were derived from a montage of 16 optodes on each side of the head. Results showed that fNIRS responses originating from auditory processing areas are highly dependent on sound intensity level: higher stimulation levels led to higher concentration changes. Caudal and rostral channels showed different waveform morphologies, reflecting specific cortical signal processing of the stimulus. Channels overlying the supramarginal and caudal superior temporal gyrus evoked a phasic response, whereas channels over Broca's area showed a broad tonic pattern. This data set can serve as a foundation for future auditory fNIRS research to develop the technique as a hearing assessment tool in the normal hearing and hearing-impaired populations.
- ItemObjective measurement of tinnitus using functional near-infrared spectroscopy and machine learning(Plos One, 2020-11) Shoushtarian, Mehrnaz; Alizadehsani, Roohallah; Khosravi, Abbas; Acevedo, Nicola; McKay, Colette; Nahavandi, Saeid; Fallon, JamesChronic tinnitus is a debilitating condition which affects 10-20% of adults and can severely impact their quality of life. Currently there is no objective measure of tinnitus that can be used clinically. Clinical assessment of the condition uses subjective feedback from individuals which is not always reliable. We investigated the sensitivity of functional near-infrared spectroscopy (fNIRS) to differentiate individuals with and without tinnitus and to identify fNIRS features associated with subjective ratings of tinnitus severity. We recorded fNIRS signals in the resting state and in response to auditory or visual stimuli from 25 individuals with chronic tinnitus and 21 controls matched for age and hearing loss. Severity of tinnitus was rated using the Tinnitus Handicap Inventory and subjective ratings of tinnitus loudness and annoyance were measured on a visual analogue scale. Following statistical group comparisons, machine learning methods including feature extraction and classification were applied to the fNIRS features to classify patients with tinnitus and controls and differentiate tinnitus at different severity levels. Resting state measures of connectivity between temporal regions and frontal and occipital regions were significantly higher in patients with tinnitus compared to controls. In the tinnitus group, temporal-occipital connectivity showed a significant increase with subject ratings of loudness. Also in this group, both visual and auditory evoked responses were significantly reduced in the visual and auditory regions of interest respectively. Naïve Bayes classifiers were able to classify patients with tinnitus from controls with an accuracy of 78.3%. An accuracy of 87.32% was achieved using Neural Networks to differentiate patients with slight/ mild versus moderate/ severe tinnitus. Our findings show the feasibility of using fNIRS and machine learning to develop an objective measure of tinnitus. Such a measure would greatly benefit clinicians and patients by providing a tool to objectively assess new treatments and patients' treatment progress.
- ItemObjective Tinnitus Measurement via fNIRS and Machine Learning(Wolters Kluwer Health, 2021-02) Shoushtarian, Mehrnaz; Alizadehsani, Roohallah; Khosravi, Abbas; Acevedo, Nicola; McKay, Colette; Nahavandi, Saeid; Fallon, James