DEL RECONOCIMIENTO A LA INSTITUCIONALIZACIÓN DE LOS IMAMES EN EUROPA.

Models of binaural localisation can be classified according to their underlying principles. Physiologically motivated methods generally draw from neurophys- iological findings, and may either simulate neural networks directly or rely on mathematical descriptions of biologically-inspired processes. Another approach is to useanalytically motivatedexpressions whose only goal is to predict the results of subjective tests. This does not mean that such expressions are merely a math- ematical fit to the data, but that they do not make any underlying assumptions based-on or even related-to physiological knowledge. Thus, analytically-motived methods are psychoacoustically plausible, whereas physiologically-motived meth- ods are also physiologically plausible. This section provides a general literature review of different strategies for modelling binaural sound localisation.

Jeffress (1948) published a landmark paper in which he described a method for sound localisation based on ITD cues. The paper is considered remarkable,

especially when recognising the little amount of knowledge that was available at the time that it was published. An extensive review of its physiological basis is available in (Yin, 2002). Jeffress made three underlying assumptions. First, he assumed that input signals from the peripheral auditory system carry reliable bin- aural timing information. Secondly, he assumed that the auditory system employs an array of binaural detection cells (equivalent to MSO neurons, see Section 2.3) which have a maximum activity when input signals coincide. Lastly, he assumed that the bilateral neural pathways conveying information to the central nervous system are formed in opposing directions. From a signal processing perspective this can be seen as a bidirectional delay line, whose intersections correspond to coincidence detectors. Since processing is performed in separate frequency chan- nels, then multiple delay lines exist, each corresponding to data in a different critical band. According to Jeffress, the place within this network in which max- imal activity occurs is inherently dependent on the ITD and corresponds to the perceived location of the sound source. From a mathematical point of view, this is equivalent to calculating a running cross-correlation function between the ipsi- lateral and contralateral signals at a frequency band of interest (Joris et al., 1998).

Lindemann (1986a; 1986b) extended Jeffress’ model by adding contralateral inhibitory elements to it. He assumed that the two signals in a bidirectional delay line inhibit one another, which resembles physiological processes of ILD encoding (see Section 2.3). In turn, this accounts for time-intensity trading mechanisms exhibited by the human auditory system. Gaik (1993) adjusted this mechanism by introducing additional weighting functions which simulate naturally occurring time-intensity combinations, thus improving the psychoacoustical plausibility of the model. Another important benefit of the contralateral inhibition process con- cerns the ability to perceive lead-lag type stimuli. In (Lindemann, 1986b), it is shown that the process leads to emphasis of the lead sound, which implies that the model can account for the precedence effect. A modelling strategy founded on coincidence detection, with all of its extensions, is often referred to as aJeffress- Lindemann-Gaik model.

Breebaart and colleagues (2001) suggested a different approach to model bin- aural hearing. Rather than relying on cross-correlation algorithms, they based their model on Equalisation-Cancellation (EC) theory (Durlach, 1963) and the physiological findings of Reed and Blum (1990). They developed a conceptual type of nerve cells, combining ITD coincidence detectors (similar to those of a Jeffress model) with ILD processors inspired by the findings of Reed and Blum. According to EC-theory, the auditory system eliminates binaural masking com- ponents in a two pass process. First, spectral and temporal transformations are applied to input stimuli in an attempt to equalise the masking components (equal- isation, or E-process). Then, one stimulus is subtracted from the other and the identical components are removed (cancellation, or C-process). Although binau- ral masking is not the main concern of this study, the EC-process implies a type of auditory signal processing approach directly relevant to sound localisation. As it is assumed that EC is accomplished by a contralateral inhibition mechanism, Breebaart and colleagues partially based their model on EI-type neurons found in the LSO and IC. The overall output of this model is somewhat complex, as analy- sis is performed in different critical bands at different instants in time. Therefore, for a single frequency band this results in a two-dimensional time varying activity pattern, describing the change of EI activity over time.

Faller and Merimaa (2004b) have suggested a single modelling approach to analyse localisation in complex listening situations, often involving multiple sources and reflections. Their model is analytically motivated and relies on evaluation of directional cues using interaural coherence. When multiple sources and reflec- tions exist, localisation cues presented to the auditory system are considerably different than in an anechoic environment. The model’s underlying assumption is that the locus of a sound source can be determined by considering localisation cues only at time instances where they resemble free field cues. This is one of the core components used in the integrated model described in this thesis, and as such, will be further detailed in Chapter 6.

ing binaural cues. In their study, they showed that due to the HRTF filtering of the outer ear, the location-specific structure of binaural signals is transformed into location-specific synchrony patterns in the brain, which may correspond to patterns of free-field localisation cues previously learned by the auditory system. Although the Goodman-Brette model seems promising and provides an in depth view of the biological processes fundamental to sound localisation, directly em- ploying their model is somewhat beyond the scope of this work, as it requires a substantial understanding of auditory neuroscience which is not within the au- thor’s background.