Abstracts of the British Society of Audiology annual conference (incorporating the Experimental and Clinical Short papers meetings)

Abstracts of the British Society of Audiology annual conference (incorporating the Experimental and Clinical Short papers meetings)s of the British Society of Audiology annual conference (incorporating the Experimental and Clinical Short papers meetings) September 7–9, 2011, NIHR National Biomedical Research Unit in Hearing, Nottingham Trent University, UK Fortnum H, Hall D, Smith S (eds) Frequency selectivity and local map structure in human auditory cortex measured with 7 Tesla fMRI C. Lanting * , S. Francis § , R. Bowtell § and K. Krumbholz* . * MRC Institute of Hearing Research, Nottingham, UK. § Sir Peter Mansfi eld Magnetic Resonance Centre, School of Physics and Astronomy, University of Nottingham, UK Neurons in the auditory pathway are topographically arranged by their response to sound frequency. This tonotopic organisation mirrors the distribution of receptors in the cochlea, with neurons at the base of the cochlea responding best to high frequencies, and neurons at the apex responding best to low frequencies. Previous functional magnetic resonance imaging (fMRI) results suggest that, in human auditory cortex, high frequencies are represented at the medial end and low frequencies in the antero-lateral end of Heschl ’ s gyrus (Formisano et al, 2003; Humphries et al, 2010). While fMRI has been used to investigate the topography of best frequency (BF) in human auditory cortex, the selectivity, or bandwidth of tuning, for frequency of auditory cortical neurons remains unknown. This work was aimed at assessing the suitability of fMRI to measure frequency selectivity in human auditory cortex. Both conventional and adaptation-based fMRI paradigms were used. Blood oxygen level-dependent (BOLD) responses were recorded with high-resolution fMRI (1 1 1 mm 3 ) at 7 Tesla (Philips Achieva) using a sparse imaging protocol. Stimuli consisted of narrow-band noises (50-Hz bandwidth), centred around nine test frequencies that varied from 500 Hz to 8 kHz in half-octave steps. Frequency tuning curves of activated voxels were derived by assigning each voxel to the frequency to which it responded best for a given proportion of trials, and then averaging the frequency responses of voxels with the same best frequency for the remaining trials. The resulting tuning curves were fi tted with a bell curve to estimate their BF and tuning bandwidth. The voxel frequency tuning curves were remarkably reliable across trials. Voxels in the area of Heschl ’ s gyrus, which is the site of primary auditory cortex in humans, tended to show sharper frequency tuning than voxels in non-primary. This would be expected based on neurophysiological data from animals. Furthermore, the tuning bandwidths also appeared to correlate with the local map structure, in that areas with homogenous frequency preference showed sharper tuning than areas with heterogeneous frequency preference. This dependency of frequency selectivity on local map structure may be a result of the spatial smoothness of BOLD effect. References Formisano, E. , Kim, D. , Di Salle, F. , van de Moortele, P.F. , Ugurbil, K. & Goebel, R. 2003. Mirror-Symmetric Tonotopic Maps in Human Primary Auditory Cortex. Neuron , 40(4), 859–869. Humphries, C. , Liebenthal, E. & Binder, J.R. 2010. Tonotopic organization of human auditory cortex. NeuroImage , 50(3), 1202–1211. Cortical processing of coded speech P.T. Hosseini , E. Sear, A. Sanderson, C. Verschuur, M. Lutman, J. Brinton and S. Wang . Hearing and Balance Centre, Institute of Sound and Vibration Research, University of Southampton, UK Investigation on neural processing of distorted speech can improve the speech processors of cochlear implants (CI) and enhance our understanding of auditory processing and hearing loss. one model has suggested a role for cortical oscillations in speech processing (Poeppel, 2003). The left anterior part of the superior temporal sulcus responds to intelligible speech and speech recognition has been shown to be associated with an increase in gamma-band activity in the left hemisphere (Hannemann et al, 2007). This study investigated the dynamics of cortical oscillations in processing speech which has been coded by speech shaped noise and a CI speech processing strategy. The BKB (Bamford-Kowal-Bench) sentences were decomposed into multiple frequency bands and vocoded with envelope matched speech-shaped noise or according to a Cl speech processing strategy. A whole-head scalp EEG was recorded while normal, CI-vocoded and noise-vocoded sentences were presented to eight otologically normal participants. Using a multiple sparse priors source reconstruction technique (Friston et al, 2008), the brain sources were identifi ed according to the induced response of energy in a frequency band of 3–120 Hz during the speech sentence presentations between 0.5 and 2.5s. The interaction between sources was further investigated using coherence analysis. The areas of the brain contributing most to the perception of normal sentences were auditory cortex, posterior cingulate cortex (PC), somatosensory association cortex (SA) and primary visual cortex (LV1 and RV1). In addition, the anterior prefrontal cortex (AP) region was involved in the other two conditions. The most involved area in all three conditions was PC. Coherence analysis illustrated high coherence between the LV1 and SA areas and between the RV1 and PC areas in the normal condition. In the CI-vocoded condition, the connection LV1-SA was reduced signifi cantly and the connection RV1-PC remained at a high level. Also, a strong connection between SA and AP emerged. The noise-vocoded condition showed similar patterns as the CI-vocoded condition. In conclusion, fi ve brain regions and their interaction may be involved in the processing of coded speech and Neural oscillations in multiple frequencies might reveal distinct patterns of brain connectivity in coded speech processing. ISSN 1499-2027 print/ISSN 1708-8186 online © 2012 British Society of Audiology, International Society of Audiology, and Nordic Audiological Society DOI: 10.3109/14992027.2012. 653103 International Journal of Audiology 2012; 51: 220–277