Central auditory processing and the acquisition of phonology in 2-year-old children with recurrent acute otitis media

Middle ear infections (acute otitis media, AOM) are among the most common infectious diseases in childhood, their incidence being greatest at the age of 6–12 months. Approximately 10–30% of children undergo repetitive periods of AOM, referred to as recurrent acute otitis media (RAOM). Middle ear fluid during an AOM episode causes, on average, 20–30 dB of hearing loss lasting from a few days to as much as a couple of months. It is well known that even a mild permanent hearing loss has an effect on language development but so far there is no consensus regarding the consequences of RAOM on childhood language acquisition. The results of studies on middle ear infections and language development have been partly discrepant and the exact effects of RAOM on the developing central auditory nervous system are as yet unknown. This thesis aims to examine central auditory processing and speech production among 2-year-old children with RAOM. Event-related potentials (ERPs) extracted from electroencephalography can be used to objectively investigate the functioning of the central auditory nervous system. For the first time this thesis has utilized auditory ERPs to study sound encoding and preattentive auditory discrimination of speech stimuli, and neural mechanisms of involuntary auditory attention in children with RAOM. Furthermore, the level of phonological development was studied by investigating the number and the quality of consonants produced by these children. Acquisition of consonant phonemes, which are harder to hear than vowels, is a good indicator of the ability to form accurate memory representations of ambient language and has not been studied previously in Finnish-speaking children with RAOM. The results showed that the cortical sound encoding was intact but the preattentive auditory discrimination of multiple speech sound features was atypical in those children with RAOM. Furthermore, their neural mechanisms of auditory attention differed from those of their peers, thus indicating that children with RAOM are atypically sensitive to novel but meaningless sounds. The children with RAOM also produced fewer consonants than their controls. Noticeably, they had a delay in the acquisition of word-medial consonants and the Finnish phoneme /s/, which is acoustically challenging to perceive compared to the other Finnish phonemes. The findings indicate the immaturity of central auditory processing in the children with RAOM, and this might also emerge in speech production. This thesis also showed that the effects of RAOM on central auditory processing are long-lasting because the children had healthy ears at the time of the study. An effective neural network for speech sound processing is a basic requisite of language acquisition, and RAOM in early childhood should be considered as a risk factor for language development.

Spectral retinal image processing and analysis for ophthalmology

Diabetic retinopathy, age-related macular degeneration and glaucoma are the leading causes of blindness worldwide. Automatic methods for diagnosis exist, but their performance is limited by the quality of the data. Spectral retinal images provide a significantly better representation of the colour information than common grayscale or red-green-blue retinal imaging, having the potential to improve the performance of automatic diagnosis methods. This work studies the image processing techniques required for composing spectral retinal images with accurate reflection spectra, including wavelength channel image registration, spectral and spatial calibration, illumination correction, and the estimation of depth information from image disparities. The composition of a spectral retinal image database of patients with diabetic retinopathy is described. The database includes gold standards for a number of pathologies and retinal structures, marked by two expert ophthalmologists. The diagnostic applications of the reflectance spectra are studied using supervised classifiers for lesion detection. In addition, inversion of a model of light transport is used to estimate histological parameters from the reflectance spectra. Experimental results suggest that the methods for composing, calibrating and postprocessing spectral images presented in this work can be used to improve the quality of the spectral data. The experiments on the direct and indirect use of the data show the diagnostic potential of spectral retinal data over standard retinal images. The use of spectral data could improve automatic and semi-automated diagnostics for the screening of retinal diseases, for the quantitative detection of retinal changes for follow-up, clinically relevant end-points for clinical studies and development of new therapeutic modalities.