Efficient coding of spectrotemporal binaural sounds leads to emergence of the auditory space representation

To date a number of studies have shown that receptive field shapes of early sensory neurons can be reproduced by optimizing coding efficiency of natural stimulus ensembles. A still unresolved question is whether the efficient coding hypothesis explains formation of neurons which explicitly represent environmental features of different functional importance. This paper proposes that the spatial selectivity of higher auditory neurons emerges as a direct consequence of learning efficient codes for natural binaural sounds. Firstly, it is demonstrated that a linear efficient coding transform - Independent Component Analysis (ICA) trained on spectrograms of naturalistic simulated binaural sounds extracts spatial information present in the signal. A simple hierarchical ICA extension allowing for decoding of sound position is proposed. Furthermore, it is shown that units revealing spatial selectivity can be learned from a binaural recording of a natural auditory scene. In both cases a relatively small subpopulation of learned spectrogram features suffices to perform accurate sound localization. Representation of the auditory space is therefore learned in a purely unsupervised way by maximizing the coding efficiency and without any task-specific constraints. This results imply that efficient coding is a useful strategy for learning structures which allow for making behaviorally vital inferences about the environment.Comment: 22 pages, 9 figure

Contributions of local speech encoding and functional connectivity to audio-visual speech perception

Seeing a speaker’s face enhances speech intelligibility in adverse environments. We investigated the underlying network mechanisms by quantifying local speech representations and directed connectivity in MEG data obtained while human participants listened to speech of varying acoustic SNR and visual context. During high acoustic SNR speech encoding by temporally entrained brain activity was strong in temporal and inferior frontal cortex, while during low SNR strong entrainment emerged in premotor and superior frontal cortex. These changes in local encoding were accompanied by changes in directed connectivity along the ventral stream and the auditory-premotor axis. Importantly, the behavioral benefit arising from seeing the speaker’s face was not predicted by changes in local encoding but rather by enhanced functional connectivity between temporal and inferior frontal cortex. Our results demonstrate a role of auditory-frontal interactions in visual speech representations and suggest that functional connectivity along the ventral pathway facilitates speech comprehension in multisensory environments

Alternative Neuropsychological and Magnetic Resonance Imaging Measures in Multiple Sclerosis: Exploring the relation between brain lesion measured by diffusion tensor magnetic resonance imaging and interhemispheric communication and processing speed in multiple sclerosis

Multiple sclerosis (MS) is a chronic neurological disease of the central nerve system that affects young adults with a higher prevalence in women (ratio 3:2). The neuropathology of the disease is characterised by demyelination of the white matter in the brain and central cord. MS may involve degeneration of white matter throughout the nervous system, with a predilection for specific target zones that includes the corpus callosum. The pathologic process may lead to motor problems, but halve of the patients has cognitive problems associated with MS. In this thesis, we focus on the cognitive problems and the relation with neuropathological brain damage. One of the brain areas preferentially involved in MS, is the corpus callosum. This brain structure is the largest white matter tract connecting both hemispheres. Research in callosotomy patients, acallosal patients and callosal section patients indicates that robust callosal damage may lead to interhemispheric transfer dysfunctions. In the first part of this thesis callosal problems in MS are explored. Damage to the corpus callosum in this patient group is subtler than in callosotomy patients. Moreover, the callosal damage strongly varies from patient to patient. In this thesis the redundancy gain paradigm, a behavioural measure to investigate interhemispheric communication is used. In this task, flashes of light are presented to the left, right or bilateral (left and right simultaneously) visual hemifield while the subject fixates to the middle of the screen. As soon as the subject detects a flash, he presses the response button with the left or right hand (detection task). An effect that is typically observed in healthy subjects is that reaction times to bilateral stimuli are faster than to unilateral stimuli. This effect is referred to as the redundancy gain effect. Previous research shows that the redundancy gain effect is enlarged in patients with callosal problems (acallosal patients or patients with callosal section). The results in this thesis show, in analogy with the results in patients with robust callosal damage, an enlarged redundancy gain effect for MS patients. These results demonstrate the sensitiveness of the redundancy gain paradigm to investigate callosal problems in MS. To explore the effect of the amount of callosal brain damage on the redundancy gain effect, the callosal damage needs to be quantified. For this purpose diffusion tensor imaging was used. With this technique, water diffusion in the white matter can be investigated. Water in the brain spreads preferentially along the direction of the axonal fibers. Intact myelin sheets are effective barriers for the water. Demyelination, an important pathological aspect of MS, leads to decreased delineation of the tracts along which the water spreads. This results in changed diffusion derived measures. Fractional anisotropy is an important diffusion derived measure for inter- and intravoxel fiber coherence. Previous research shows that fractional anisotropy is decreased in MS patients compared to healthy controls. To calculate the fractional anisotropy, diffusion measures along three directions are defined, more specific along the principal direction, along the direction of minimal diffusion and along a third Alternative Neuropsychological and MRI Measures in MS 89 Summary direction that is orthogonal to the previous two. With this information, the longitudinal and transverse diffusivity can be calculated. Longitudinal diffusivity is the diffusion eigenvalue along the principal direction, whereas the transverse diffusivity is the mean of the eigenvalues along the other two directions. Recent research shows that demyelination and axonal loss, specific for MS pathology, is characterised by increased transverse diffusivity. Hence, transverse diffusivity is a unique marker for MS. The results of this thesis confirm this and show that transverse diffusivity is significantly more increased than longitudinal diffusivity in MS patients compared to healthy matched controls. Thirdly, a correlation between the behavioural results, the redundancy gain effect, and the brain imaging measures, the diffusion derived measures, was found: the larger the transverse diffusivity, or in other words, the MS related callosal damage, the larger the redundancy gain effect in MS patients. Moreover, neither longitudinal diffusivity, nor callosal lesion load as defined on conventional T2 images were additional factors in explaining this correlation. The results of the first part of this thesis show a) that the redundancy gain paradigm is a sensitive measure to investigate callosal brain damage in MS, b) that diffusion derived parameters are subtle measures to indicate MS related brain damage and c) that a significant correlation between callosal brain damage and the redundancy gain effect could be found in MS patients. In the second part of this thesis the focus was on the relation between cerebral brain damage as defined by diffusion derived measures and information processing speed in MS. Information processing speed is a cognitive measure tested by the Paced Serial Addition Test (PASAT) and the Symbol Digit Modalities Test (SDMT), two commonly used neuropsychological tests in MS. A significant correlation between the performance on the SDMT and transverse diffusivity in the whole brain was found in MS patients, indicating that demyelination and axonal damage, characteristic for MS pathology, are important factors for explaining the slowed information processing speed in MS. No correlation was found with the performance on the PASAT, which can be explained by the weaker psychometric qualities of the PASAT compared to the SDMT. First of all, the results of this thesis corroborate the heterogeneous pathological condition in MS. Research on callosal problems in MS can not be done without considering these individual differences. Based on our results, diffusion weighted imaging seems to offer a promising technique to determine cerebral damage in MS. Transverse diffusivity, considered to be a unique benchmark of white matter demyelination as seen in MS, is of special interest. Moreover, this diffusion derived measures correlate with cognitive (dys)function in MS, a correlation not consistently found for conventional imaging (lesion load on T2 of T1 images)

Efficient Coding and Statistically Optimal Weighting of Covariance among Acoustic Attributes in Novel Sounds

To the extent that sensorineural systems are efficient, redundancy should be extracted to optimize transmission of information, but perceptual evidence for this has been limited. Stilp and colleagues recently reported efficient coding of robust correlation (r = .97) among complex acoustic attributes (attack/decay, spectral shape) in novel sounds. Discrimination of sounds orthogonal to the correlation was initially inferior but later comparable to that of sounds obeying the correlation. These effects were attenuated for less-correlated stimuli (r = .54) for reasons that are unclear. Here, statistical properties of correlation among acoustic attributes essential for perceptual organization are investigated. Overall, simple strength of the principal correlation is inadequate to predict listener performance. Initial superiority of discrimination for statistically consistent sound pairs was relatively insensitive to decreased physical acoustic/psychoacoustic range of evidence supporting the correlation, and to more frequent presentations of the same orthogonal test pairs. However, increased range supporting an orthogonal dimension has substantial effects upon perceptual organization. Connectionist simulations and Eigenvalues from closed-form calculations of principal components analysis (PCA) reveal that perceptual organization is near-optimally weighted to shared versus unshared covariance in experienced sound distributions. Implications of reduced perceptual dimensionality for speech perception and plausible neural substrates are discussed

Effects of dichotic auditory training on children with central auditory processing disorder

(Central) auditory processing disorder (CAPD) is a condition in which individuals with normal hearing present with difficulties often associated with hearing loss. While there are currently many tests available for the CAPD assessment, there are very few therapies for the remediation of a CAPD. A new therapy program, called Dichotic Auditory Training (DAT), aimed at improving the performance of those individuals with CAPD, was the focus of this study. Eight children between the ages of seven and twelve went through the four week training. The Staggered Spondaic Word (SSW) test, the SCAN-C/A, and a test designed after the DAT were given prior to and immediately following training. The results from these tests were analyzed for statistically significant differences between pre- and post-testing. Statistically significant results were yielded for six of the nineteen different testing conditions. All conditions that yielded statistically significant were those associated with the dichotic presentation of words. These results are thought to be reflective of plastic changes occurring within the central auditory systems, and a direct result of the training the subjects underwent. The results from this study offer much promise for the future of the remediation of CAPD

Behavioral and electrophysiological assessment of children with a specific temporal processing disorder

Auditory processing disorders (APDs) have received considerable attention over the past few decades. Much of the attention has focused on the controversy surrounding the operational definition of APD, the heterogeneous nature of APD, and an appropriate test battery for APD assessment. Temporal processing deficits are one characteristic of APD and are the focus of the present investigation. This investigation reports behavioral and early electrophysiological measures in a group of children with specific temporal processing difficulties and an age-matched control group. In an effort to better describe the subjects, two language tests and the SCAN-C were administered. Significant differences were found in the language tests, SCAN-C, and behavioral tests of temporal processing. No significant differences in ABR waveform latency were found between the control and experimental group. Significant amplitude differences were found, albeit small. Binaural interaction was present in both groups. Based on the results of the present well-controlled investigation of children with temporal processing disorders, there is no indication that the auditory brainstem response recording to click stimuli is efficient in providing additional diagnosis of APD

Functional Sensory Representations of Natural Stimuli: the Case of Spatial Hearing

In this thesis I attempt to explain mechanisms of neuronal coding in the auditory system as a form of adaptation to statistics of natural stereo sounds. To this end I analyse recordings of real-world auditory environments and construct novel statistical models of these data. I further compare regularities present in natural stimuli with known, experimentally observed neuronal mechanisms of spatial hearing. In a more general perspective, I use binaural auditory system as a starting point to consider the notion of function implemented by sensory neurons. In particular I argue for two, closely-related tenets: 1. The function of sensory neurons can not be fully elucidated without understanding statistics of natural stimuli they process. 2. Function of sensory representations is determined by redundancies present in the natural sensory environment. I present the evidence in support of the first tenet by describing and analysing marginal statistics of natural binaural sound. I compare observed, empirical distributions with knowledge from reductionist experiments. Such comparison allows to argue that the complexity of the spatial hearing task in the natural environment is much higher than analytic, physics-based predictions. I discuss the possibility that early brain stem circuits such as LSO and MSO do not \"compute sound localization\" as is often being claimed in the experimental literature. I propose that instead they perform a signal transformation, which constitutes the first step of a complex inference process. To support the second tenet I develop a hierarchical statistical model, which learns a joint sparse representation of amplitude and phase information from natural stereo sounds. I demonstrate that learned higher order features reproduce properties of auditory cortical neurons, when probed with spatial sounds. Reproduced aspects were hypothesized to be a manifestation of a fine-tuned computation specific to the sound-localization task. Here it is demonstrated that they rather reflect redundancies present in the natural stimulus. Taken together, results presented in this thesis suggest that efficient coding is a strategy useful for discovering structures (redundancies) in the input data. Their meaning has to be determined by the organism via environmental feedback

Computational analysis of the synergy among multiple interacting genes

Diseases such as cancer are often related to collaborative effects involving interactions of multiple genes within complex pathways, or to combinations of multiple SNPs. To understand the structure of such mechanisms, it is helpful to analyze genes in terms of the purely cooperative, as opposed to independent, nature of their contributions towards a phenotype. Here, we present an information-theoretic analysis that provides a quantitative measure of the multivariate synergy and decomposes sets of genes into submodules each of which contains synergistically interacting genes. When the resulting computational tools are used for the analysis of gene expression or SNP data, this systems-based methodology provides insight into the biological mechanisms responsible for disease