Dissociation of first- and second-order motion systems by perceptual learning

Published in final edited form as: Atten Percept Psychophys. 2012 July ; 74(5): 1009–1019. doi:10.3758/s13414-012-0290-3.Previous studies investigating transfer of perceptual learning between luminance-defined (LD) motion and texture-contrast-defined (CD) motion tasks have found little or no transfer from LD to CD motion tasks but nearly perfect transfer from CD to LD motion tasks. Here, we introduce a paradigm that yields a clean double dissociation: LD training yields no transfer to the CD task, but more interestingly, CD training yields no transfer to the LD task. Participants were trained in two variants of a global motion task. In one (LD) variant, motion was defined by tokens that differed from the background in mean luminance. In the other (CD) variant, motion was defined by tokens that had mean luminance equal to the background but differed from the background in texture contrast. The task was to judge whether the signal tokens were moving to the right or to the left. Task difficulty was varied by manipulating the proportion of tokens that moved coherently across the four frames of the stimulus display. Performance in each of the LD and CD variants of the task was measured as training proceeded. In each task, training produced substantial improvement in performance in the trained task; however, in neither case did this improvement show any significant transfer to the nontrained task.This work was supported in part by NSF Award BCS-0843897 to Dr. Chubb and in part by Award Number RO1NS064100 from the National Institutes of Health, National Institute of Neurological Disorders and Stroke to Dr. Vaina. (BCS-0843897 - NSF; RO1NS064100 - National Institutes of Health, National Institute of Neurological Disorders and Stroke)Accepted manuscrip

Multivoxel codes for representing and integrating acoustic features in human cortex

Using fMRI and multivariate pattern analysis, we determined whether acoustic features are represented by independent or integrated neural codes in human cortex. Male and female listeners heard band-pass noise varying simultaneously in spectral (frequency) and temporal (amplitude-modulation [AM] rate) features. In the superior temporal plane, changes in multivoxel activity due to frequency were largely invariant with respect to AM rate (and vice versa), consistent with an independent representation. In contrast, in posterior parietal cortex, neural representation was exclusively integrated and tuned to specific conjunctions of frequency and AM features. Direct between-region comparisons show that whereas independent coding of frequency and AM weakened with increasing levels of the hierarchy, integrated coding strengthened at the transition between non-core and parietal cortex. Our findings support the notion that primary auditory cortex can represent component acoustic features in an independent fashion and suggest a role for parietal cortex in feature integration and the structuring of acoustic input. Significance statement A major goal for neuroscience is discovering the sensory features to which the brain is tuned and how those features are integrated into cohesive perception. We used whole-brain human fMRI and a statistical modeling approach to quantify the extent to which sound features are represented separately or in an integrated fashion in cortical activity patterns. We show that frequency and AM rate, two acoustic features that are fundamental to characterizing biological important sounds such as speech, are represented separately in primary auditory cortex but in an integrated fashion in parietal cortex. These findings suggest that representations in primary auditory cortex can be simpler than previously thought and also implicate a role for parietal cortex in integrating features for coherent perception

Intraparietal sulcus maintains working memory representations of somatosensory categories in an adaptive, context-dependent manner

Working memory (WM) representations are generally known to be influenced by task demands, but it is not clear whether this extends to the somatosensory domain. One way to investigate the influence of task demands is with categorization paradigms, wherein either a single stimulus or an associated category is maintained in WM. In the somatosensory modality, category representations have been identified in the premotor cortex (PMC) and the intraparietal sulcus (IPS). In this study we used multivariate-pattern-analysis with human fMRI data to investigate whether the WM representations in the PMC, IPS or other regions are influenced by changing task demands. We ensured the task-dependent, categorical WM information was decorrelated from stimulus features by (1) teaching participants arbitrary, non-rule based stimulus groupings and (2) contrasting identical pairs of stimuli across experimental conditions, where either a single stimulus or the associated group was maintained in WM. Importantly, we also decoupled the decision and motor output from the WM representations. With these experimental manipulations, we were able to pinpoint stimulus-specific WM information to the left frontal and parietal cortices and context-dependent, group-specific WM information to the left IPS. By showing that grouped stimuli are represented more similarly in the Group condition than in the Stimulus condition, free from stimulus and motor output confounds, we provide novel evidence for the adaptive nature of somatosensory WM representations in the IPS with changing task-demands

Background prior-based salient object detection via deep reconstruction residual

Detection of salient objects from images is gaining increasing research interest in recent years as it can substantially facilitate a wide range of content-based multimedia applications. Based on the assumption that foreground salient regions are distinctive within a certain context, most conventional approaches rely on a number of hand designed features and their distinctiveness measured using local or global contrast. Although these approaches have shown effective in dealing with simple images, their limited capability may cause difficulties when dealing with more complicated images. This paper proposes a novel framework for saliency detection by first modeling the background and then separating salient objects from the background. We develop stacked denoising autoencoders with deep learning architectures to model the background where latent patterns are explored and more powerful representations of data are learnt in an unsupervised and bottom up manner. Afterwards, we formulate the separation of salient objects from the background as a problem of measuring reconstruction residuals of deep autoencoders. Comprehensive evaluations on three benchmark datasets and comparisons with 9 state-of-the-art algorithms demonstrate the superiority of the proposed work

The Perception of Surface Properties: Translucence and Gloss

The human visual system is sensitive to differences in gloss and translucence, two optical properties which are found in conjunction in many natural materials. They are driven by similar underlying physical properties of light transport - the degree to which light is scattered from the surface of a material, or within the material. This thesis aimed to address some fundamental questions about how gloss and translucence are perceived. Two psychophysical methods (maximum likelihood difference scaling, and conjoint measurement) were used throughout, as they provided an appropriate way of investigating how perceptual experiences related to physical variables. In the introduction, I review the literature on the perception of gloss and translucence. Study 1 investigated the relationship between variables controlling light transport in translucent volumes and percepts of translucence. The results show that translucence perception is not based on estimates of light transport properties per se, but probably uses spatially-related statistical pseudocues in conjunction with other cues. Study 2 examined a similar issue, but the translucent material was presented as a layer enveloping a solid object. Behavioural responses were similar for these translucent materials, which were perceived as glossy layers of coating. Study 3 further explored established findings that perceived translucence shows inconstancy under changes in viewing condition. Perceived translucence was dependent in a complex way on both light-scattering in the material and illumination direction in both volumes and layers of translucent materials. Study 4 used similar layers of subsurface light-scattering and -absorbing material and applied them to multiple base materials. Opacity and a lack of mirror-like reflections enabled observers to make the most accurate independent judgements of darkness and cloudiness. Study 5 explored observers' sensitivity to spatial variation of scatter across a surface using similar layers of coating, and the way in which observers might weight cues differently to answer subtly different questions (judgements of 'shininess' vs. 'cleanliness'). Layer thickness and variation of scatter significantly affected perceived shine and cleanliness, with layer thickness influencing decisions more than variation. Scatter variation contributed to decisions significantly more for judgements of cleanliness than shine. Study 6 investigated how tactile surface roughness influenced perceived gloss. Previous findings have shown that tactile compliance and friction influence perceived gloss, and that friction interacts with visual gloss. Our results showed that surface roughness and visual gloss both affected perceived gloss, but there was no interaction, suggesting that different types of haptic information are combined with visual information differently. Finally, study 7 explored the potential cortical basis of perceived translucence. Through testing a neuropsychological patient, we showed that perceived translucence is dependent on cortical areas not responsible for colour or texture discrimination. The thesis concludes with a discussion of additional recent findings, the implications of the research reported in this thesis, and proposals for future research

Backwards is the way forward: feedback in the cortical hierarchy predicts the expected future

Clark offers a powerful description of the brain as a prediction machine, which offers progress on two distinct levels. First, on an abstract conceptual level, it provides a unifying framework for perception, action, and cognition (including subdivisions such as attention, expectation, and imagination). Second, hierarchical prediction offers progress on a concrete descriptive level for testing and constraining conceptual elements and mechanisms of predictive coding models (estimation of predictions, prediction errors, and internal models)

Representation of statistical sound properties in human auditory cortex

The work carried out in this doctoral thesis investigated the representation of statistical sound properties in human auditory cortex. It addressed four key aspects in auditory neuroscience: the representation of different analysis time windows in auditory cortex; mechanisms for the analysis and segregation of auditory objects; information-theoretic constraints on pitch sequence processing; and the analysis of local and global pitch patterns. The majority of the studies employed a parametric design in which the statistical properties of a single acoustic parameter were altered along a continuum, while keeping other sound properties fixed. The thesis is divided into four parts. Part I (Chapter 1) examines principles of anatomical and functional organisation that constrain the problems addressed. Part II (Chapter 2) introduces approaches to digital stimulus design, principles of functional magnetic resonance imaging (fMRI), and the analysis of fMRI data. Part III (Chapters 3-6) reports five experimental studies. Study 1 controlled the spectrotemporal correlation in complex acoustic spectra and showed that activity in auditory association cortex increases as a function of spectrotemporal correlation. Study 2 demonstrated a functional hierarchy of the representation of auditory object boundaries and object salience. Studies 3 and 4 investigated cortical mechanisms for encoding entropy in pitch sequences and showed that the planum temporale acts as a computational hub, requiring more computational resources for sequences with high entropy than for those with high redundancy. Study 5 provided evidence for a hierarchical organisation of local and global pitch pattern processing in neurologically normal participants. Finally, Part IV (Chapter 7) concludes with a general discussion of the results and future perspectives

The Strength of the Mind: Essays on Consciousness and Introspection

I defend the view that mental states have degrees of strength. Our pains are more or less intense, our mental imagery is more or less vivid, our visual perceptions are more or less striking, and our desires and thoughts are more or less gripping. Mental strength is a phenomenal magnitude shared by all conscious experiences that determines their degree of felt intensity. Mental strength, however, has been largely ignored over other aspects of mental states such as their representational contents, phenomenology, or type. Considering mental strength is crucial for illuminating philosophical discussions related to representationalism, the transparency of experiences, cognitive phenomenology, attention, and the structure and function of consciousness. I use mental strength to develop in detail a neuropsychologically plausible theory of introspection and its limits that is inspired by a signal detection theoretic model of perception. In the second half of the dissertation, I look into methodological issues concerning the neural correlates of consciousness such as controlling for performance capacity and stimulus strength, and what these methodological concerns reveal about our theories of consciousness and its function

A Computational Model of Auditory Feature Extraction and Sound Classification

This thesis introduces a computer model that incorporates responses similar to those found in the cochlea, in sub-corticai auditory processing, and in auditory cortex. The principle aim of this work is to show that this can form the basis for a biologically plausible mechanism of auditory stimulus classification. We will show that this classification is robust to stimulus variation and time compression. In addition, the response of the system is shown to support multiple, concurrent, behaviourally relevant classifications of natural stimuli (speech). The model incorporates transient enhancement, an ensemble of spectro - temporal filters, and a simple measure analogous to the idea of visual salience to produce a quasi-static description of the stimulus suitable either for classification with an analogue artificial neural network or, using appropriate rate coding, a classifier based on artificial spiking neurons. We also show that the spectotemporal ensemble can be derived from a limited class of 'formative' stimuli, consistent with a developmental interpretation of ensemble formation. In addition, ensembles chosen on information theoretic grounds consist of filters with relatively simple geometries, which is consistent with reports of responses in mammalian thalamus and auditory cortex. A powerful feature of this approach is that the ensemble response, from which salient auditory events are identified, amounts to stimulus-ensemble driven method of segmentation which respects the envelope of the stimulus, and leads to a quasi-static representation of auditory events which is suitable for spike rate coding. We also present evidence that the encoded auditory events may form the basis of a representation-of-similarity, or second order isomorphism, which implies a representational space that respects similarity relationships between stimuli including novel stimuli