Browsing by Author "Yarali, Mehmet"

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    Comparison of Regularity Detection between Individuals with and without Speech-in-Noise Problems using Electrophysiological Methods
    (2016) Yarali, Mehmet; Yagcioglu, Suha; Guven, Ayse Gul; Aksoy, Songul; 27810845
    OBJECTIVE: To analyze the cortical representations of auditory regularities and the relation between these representations and speech-in-noise (SIN) abilities and to compare two groups of participants with different SIN abilities on these cortical measures. MATERIALS and METHODS: In total, 22 participants aged 20-40 years with normal hearing and without noise exposure, brain stem level-processing issues, neurological/psychiatric issues, or related medication were presented with three different stimuli resembling auditory regularities appearing after random sounds as well as a random series of sounds. Participants received a total of 480 stimuli in passive and active phases each (in which they actively detected regularities). Evoked responses were recorded via 20-channel standard electroencephalography (EEG) cap. RESULTS: The groups were not significantly different in terms of evoked potential parameters. A significant negative correlation was observed between amplitudes of responses evoked by decreasing the frequency regularity in the active phase and SIN scores. Response parameters were significantly different between the stimuli. Active phase latencies were shorter and amplitudes were higher than passive phase ones, except for two stimuli. CONCLUSION: Cortical representations of decreasing frequency regularity are promising for revealing the link between SIN and representations of regularity detection. This paradigm is suggested to applicable to individuals with clinical-level SIN problems [hearing aid (HA) and cochlear implant (CI) users, normal-hearing individuals, children with learning problems, children with dyslexia, and others] to reveal which process of SIN mechanism is defective; this is a complicated process with many sub-mechanisms. These results may be utilized in designing CI and HA algorithms (for more robust representations of auditory regularities) and rehabilitation programs.