A comparative study of eight human auditory models of monaural processing

A number of auditory models have been developed using diverging approaches, either physiological or perceptual, but they share comparable stages of signal processing, as they are inspired by the same constitutive parts of the auditory system. We compare eight monaural models that are openly accessible in the Auditory Modelling Toolbox. We discuss the considerations required to make the model outputs comparable to each other, as well as the results for the following model processing stages or their equivalents: Outer and middle ear, cochlear filter bank, inner hair cell, auditory nerve synapse, cochlear nucleus, and inferior colliculus. The discussion includes a list of recommendations for future applications of auditory models.Comment: Revision 1 of the manuscrip

Sound processing in the mouse auditory cortex: organization, modulation, and transformation

The auditory system begins with the cochlea, a frequency analyzer and signal amplifier with exquisite precision. As neural information travels towards higher brain regions, the encoding becomes less faithful to the sound waveform itself and more influenced by non-sensory factors such as top-down attentional modulation, local feedback modulation, and long-term changes caused by experience. At the level of auditory cortex (ACtx), such influences exhibit at multiple scales from single neurons to cortical columns to topographic maps, and are known to be linked with critical processes such as auditory perception, learning, and memory. How the ACtx integrates a wealth of diverse inputs while supporting adaptive and reliable sound representations is an important unsolved question in auditory neuroscience. This dissertation tackles this question using the mouse as an animal model. We begin by describing a detailed functional map of receptive fields within the mouse ACtx. Focusing on the frequency tuning properties, we demonstrated a robust tonotopic organization in the core ACtx fields (A1 and AAF) across cortical layers, neural signal types, and anesthetic states, confirming the columnar organization of basic sound processing in ACtx. We then studied the bottom-up input to ACtx columns by optogenetically activating the inferior colliculus (IC), and observed feedforward neuronal activity in the frequency-matched column, which also induced clear auditory percepts in behaving mice. Next, we used optogenetics to study layer 6 corticothalamic neurons (L6CT) that project heavily to the thalamus and upper layers of ACtx. We found that L6CT activation biases sound perception towards either enhanced detection or discrimination depending on its relative timing with respect to the sound, a process that may support dynamic filtering of auditory information. Finally, we optogenetically isolated cholinergic neurons in the basal forebrain (BF) that project to ACtx and studied their involvement in columnar ACtx plasticity during associative learning. In contrast to previous notions that BF just encodes reward and punishment, we observed clear auditory responses from the cholinergic neurons, which exhibited rapid learning-induced plasticity, suggesting that BF may provide a key instructive signal to drive adaptive plasticity in ACtx

Evaluating the predictions of objective intelligibility metrics for modified and synthetic speech

Several modification algorithms that alter natural or synthetic speech with the goal of improving intelligibility in noise have been proposed recently. A key requirement of many modification techniques is the ability to predict intelligibility, both offline during algorithm development, and online, in order to determine the optimal modification for the current noise context. While existing objective intelligibility metrics (OIMs) have good predictive power for unmodified natural speech in stationary and fluctuating noise, little is known about their effectiveness for other forms of speech. The current study evaluated how well seven OIMs predict listener responses in three large datasets of modified and synthetic speech which together represent 396 combinations of speech modification, masker type and signal-to-noise ratio. The chief finding is a clear reduction in predictive power for most OIMs when faced with modified and synthetic speech. Modifications introducing durational changes are particularly harmful to intelligibility predictors. OIMs that measure masked audibility tend to over-estimate intelligibility in the presence of fluctuating maskers relative to stationary maskers, while OIMs that estimate the distortion caused by the masker to a clean speech prototype exhibit the reverse pattern

Évidences psychophysiques que l’information visuelle de bas niveau peut influencer les interférences en mémoire à long terme

Ce mémoire démontre que les caractéristiques de niveau inférieur telles que les fréquences spatiales (SF) et les orientations (V1) sont encodées spécifiquement avec les caractéristiques visuelles de niveau supérieur auxquelles elles ont été associées lors de l'apprentissage. Deux groupes ont appris deux ensembles de visages - composés soit de la même combinaison soit de deux combinaisons différentes de SF et d'orientations entre les ensembles. Plus tard, dans une tâche à trois alternatives, les participants ont distingué les visages appris des deux ensembles et des nouveaux ensembles de visages non cibles (filtrés avec trois filtres complémentaires de bas niveau). Il existe des preuves extrêmement solides que la similarité de bas niveau entre les deux ensembles appris augmente les interférences de la mémoire de reconnaissance (BF01 : 4,1; p<0.01) et il existe également des preuves solides que la similarité de bas niveau observée avec les nouvelles fonctionnalités de haut niveau n'a pas d'impact sur les interférences (BF01 : Inf; p=1). Nos résultats expliquent les contradictions apparentes dans la littérature, démontrent une directionnalité évidente dans le modèle d'encodage de la mémoire humaine et aident à consolider la relation entre l'esprit humain et les réseaux de neurones profonds.This study demonstrates that lower level features like spatial-frequencies and orientations (V1) are encoded specifically with the higher level visual features they were associated with during learning. Two groups learned two sets of faces − composed either of the same or of two different combinations of SF and orientations between the sets. Later, in a task with three alternatives, the participants distinguished the learned faces from the two sets and new non-target face sets (filtered with three low-level complementary filters). There is extremely strong evidence that the low-level similarity between the two learned sets increases recognition memory interference (BF10: 4,1355; p<0.01) and there is also strong evidence that low-level similarity seen with new high-level features is not impacting interferences (BF01: Inf; p=1). Our findings explain apparent contradictions in the litterature, demonstrate an evident directionality in the human memory encoding model and help consolidate the relation between the human mind and deep neural networks