Study Of Human Perception Research Articles

Computational Mechanisms for Perceptual Stability using Disparity and Motion Parallax.

Walking and other forms of self-motion create global motion patterns across our eyes. With the resulting stream of visual signals, how do we perceive ourselves as moving through a stable world? Although the neural mechanisms are largely unknown, human studies (Warren and Rushton, 2009) provide strong evidence that the visual system is capable of parsing the global motion into two components: one due to self-motion and the other due to independently moving objects. In the present study, we use computational modeling to investigate potential neural mechanisms for stabilizing visual perception during self-motion that build on neurophysiology of the middle temporal (MT) and medial superior temporal (MST) areas. One such mechanism leverages direction, speed, and disparity tuning of cells in dorsal MST (MSTd) to estimate the combined motion parallax and disparity signals attributed to the observer's self-motion. Feedback from the most active MSTd cell subpopulations suppresses motion signals in MT that locally match the preference of the MSTd cell in both parallax and disparity. This mechanism combined with local surround inhibition in MT allows the model to estimate self-motion while maintaining a sparse motion representation that is compatible with perceptual stability. A key consequence is that after signals compatible with the observer's self-motion are suppressed, the direction of independently moving objects is represented in a world-relative rather than observer-relative reference frame. Our analysis explicates how temporal dynamics and joint motion parallax-disparity tuning resolve the world-relative motion of moving objects and establish perceptual stability. Together, these mechanisms capture findings on the perception of object motion during self-motion.SIGNIFICANCE STATEMENT The image integrated by our eyes as we move through our environment undergoes constant flux as trees, buildings, and other surroundings stream by us. If our view can change so radically from one moment to the next, how do we perceive a stable world? Although progress has been made in understanding how this works, little is known about the underlying brain mechanisms. We propose a computational solution whereby multiple brain areas communicate to suppress the motion attributed to our movement relative to the stationary world, which is often responsible for a large proportion of the flux across the visual field. We simulated the proposed neural mechanisms and tested model estimates using data from human perceptual studies.

Human Attitude toward Reptiles: A Relationship between Fear, Disgust, and Aesthetic Preferences.

Simple SummaryAlthough there are many articles about reptiles, no one has ever studied the human perception of reptiles as a whole, a group that would include representatives of different taxonomic clades. Thus, we designed a study of human perception of all reptiles focusing on the relationship between perceived fear, disgust, and aesthetic preferences. Respondents evaluated various reptile images and the results revealed that people tend to perceive them as two clearly distinct groups based on their similar morphotype—legless reptiles (incl. snakes) and other reptiles with legs. In the case of snakes, the most feared species also tend to be perceived as beautiful. Compared to the most feared reptiles with legs (lizards, turtle, crocodiles), the legless once tend to be perceived as more disgusting. In both groups, species perceived as the least beautiful were the same as those rated as the most disgusting. Thus, reptiles cannot be rated as both beautiful and disgusting at the same time.Focusing on one group of animals can bring interesting results regarding our attitudes toward them and show the key features that our evaluation of such animals is based on. Thus, we designed a study of human perception of all reptiles focusing on the relationship between perceived fear, disgust, and aesthetic preferences and differences between snakes and other reptiles. Two sets containing 127 standardized photos of reptiles were developed, with one species per each subfamily. Respondents were asked to rate the animals according to fear, disgust, and beauty on a seven-point Likert scale. Evaluation of reptile species shows that people tend to perceive them as two clearly distinct groups based on their similar morphotype. In a subset of lizards, there was a positive correlation between fear and disgust, while disgust and fear were both negatively correlated with beauty. Surprisingly, a positive correlation between fear and beauty of snakes was revealed, i.e., the most feared species also tend to be perceived as beautiful. Snakes represent a distinct group of animals that is also reflected in the theory of attentional prioritization of snakes as an evolutionary relevant threat.

Merleau-Ponty’s Phenomenology as a Hermeneutic Framework for Quantum Mechanics

We propose a synthetic description of Merleau-Ponty’s phenomenology with the aim of providing physicists and philosophers with an alternative linguistic and conceptual framework to address the logical and ontological problematics emerged in quantum mechanics. Phenomenology’s cognitive devices such as the dynamical relationship between object and horizon, the presumptive synthesis and the constitution of an ontology based on the indivisibility of object and subject, not only show hermeneutic efficacy when applied to the study of human perception, but may prove to be sufficiently innovative to lead to novel insights towards the understanding of the quantum mechanical theoretical structure: the traditional tenet of quantum physics being in discontinuity with the major characteristics of classical physics is shaken at its fundaments and a new perspective of continuity between the two worlds is opened.

Reflections on glass

An important phenomenon in the study of human perception is the ability of observers to identify different types of surface materials. The present article will consider a wide range of factors that can influence the perceptual identification of glass, including the structural complexity of an object, whether it is hollow or solid, and the pattern of illumination. Several illumination techniques used in the field of photography are described, and examples are provided to show how they interact with structural complexity. A single psychophysical experiment is reported to evaluate the perceptions of naïve observers using a novel categorization task designed to assess potential confusions among multiple material categories. Finally, the paper will enumerate a number of specific image features that are potentially diagnostic for the identification of glass, and it will evaluate their relative importance for human perception.

A Novel Dynamic Morphed Stimuli Set to Assess Sensitivity to Identity and Emotion Attributes in Faces.

Face-based tasks are used ubiquitously in the study of human perception and cognition. Video-based (dynamic) face stimuli are increasingly utilized by researchers because they have higher ecological validity than static images. However, there are few ready-to-use dynamic stimulus sets currently available to researchers that include non-emotional and non-face control stimuli. This paper outlines the development of three original dynamic stimulus sets: a set of emotional faces (fear and disgust), a set of non-emotional faces, and a set of car animations. Morphing software was employed to vary the intensity of the expression shown and to vary the similarity between actors. Manipulating these dimensions permits us to create tasks of varying difficulty that can be optimized to detect more subtle differences in face-processing ability. Using these new stimuli, two preliminary experiments were conducted to evaluate different aspects of facial identity recognition, emotion recognition, and non-face object discrimination. Results suggest that these five different tasks successfully avoided floor and ceiling effects in a healthy sample. A second experiment found that dynamic versions of the emotional stimuli were recognized more accurately than static versions, both for labeling, and discrimination paradigms. This indicates that, like previous emotion-only stimuli sets, the use of dynamic stimuli confers an advantage over image-based stimuli. These stimuli therefore provide a useful resource for researchers looking to investigate both emotional and non-emotional face-processing using dynamic stimuli. Moreover, these stimuli vary across crucial dimensions (i.e., face similarity and intensity of emotion) which allows researchers to modify task difficulty as required.

Sustained response to symmetry in extrastriate areas after stimulus offset: An EEG study

Electrophysiological (EEG) studies of human perception have found that amplitude at posterior electrodes is more negative for symmetrical patterns compared to asymmetrical patterns. This negativity lasts for hundreds of milliseconds and it has been called sustained posterior negativity (SPN). Symmetry activates a network of visual areas, including the lateral occipital complex (LOC). The SPN is a response to presence of symmetry in the image. Given the sustained nature of this activation, in this study we tested the persistence of the SPN after stimulus offset. Two shapes were presented (for 0.5 s each) with a 1 s blank interval in between. We observed a sustained response after stimulus offset, irrespective of whether the task required processing of shape information. This supports the idea that the response to symmetry is generated by information in the image, independently of task, and that it is sustained over approximately one second post stimulus onset.

Landscape features and potential heat hazard threat: a spatial–temporal analysis of two urban universities

Urban universities are a microcosm of urban built-up areas, such as cities, but with a much smaller scale of spatial resolution. Within universities, there are many types of landscape features exhibiting different heat absorption and transmission capacities. These landscape features generate spatial–temporal heat signatures, and the knowledge about landscape features and urban heat hazard on university campuses is limited. The objective of this research is an assessment of landscape features and the potential heat hazard threats of two urban universities in ASEAN, located in the centre of the equatorial region. The focus of this research is on urban heat hazards in two urban universities in ASEAN, the University of Malaysia in Kuala Lumpur and the University of Indonesia in Jakarta, within the context of the spatial–temporal behaviour of urban heat and the urban heat effects on the environment and human well-being on campuses. The spatial and temporal analysis used to answer the objective of this research via data-gathering methods from image satellite, ground trough, and human perception study. The UM campus and UI campus, both urban campuses, had similar landscape features but had different total percentage areas of these features. The UM campus was 59.1% covered by the densely vegetated surface landscape feature, a percentage lower than that of the UI campus, which was 65.3% vegetation covered. The temporal results for the UHS of the UM campus in 2013–2016 show a maximum temperature of 39 °C. Therefore, the UHS of the UI campus demonstrated temporal behaviour in 2013–2016, with a maximum temperature of 38 °C. The UHS behaviour of the UM campus and UI campus had an air surface temperature with a maximum average temperature of 33 °C. The air surface temperatures exceeding 32 °C at the UM campus (12 pm until 6 pm = 5 h) lasted for a longer time than those at the UI campus (12 pm until 3 pm = 3 h). This study showed that, based on the perceptions on both campuses, if temperatures exceeded 30 °C, respondents were very hot and very uncomfortable, which will impact health and decrease work or academic achievements, as perceptions of heat intensity impact human well-being. Students perceived that heat intensity impacted their health and they reported becoming tired and lethargic under maximum temperatures and were very hot and very uncomfortable, and this condition impacted their work activity. These results indicated that, at both the UM and UI campuses, heat intensity impacts human well-being, with risks associated with hot temperatures. These two urban campuses are significant for ASEAN university awareness of the urban heat hazard of the equatorial area.

Calibrating facial morphs for use as stimuli in biological studies of social perception

Studies of human social perception become more persuasive when the behavior of raters can be separated from the variability of the stimuli they are rating. We prototype such a rigorous analysis for a set of five social ratings of faces varying by body fat percentage (BFP). 274 raters of both sexes in three age groups (adolescent, young adult, senior) rated five morphs of the same averaged facial image warped to the positions of 72 landmarks and semilandmarks predicted by linear regression on BFP at five different levels (the average, ±2 SD, ±5 SD). Each subject rated all five morphs for maturity, dominance, masculinity, attractiveness, and health. The patterns of dependence of ratings on the BFP calibration differ for the different ratings, but not substantially across the six groups of raters. This has implications for theories of social perception, specifically, the relevance of individual rater scale anchoring. The method is also highly relevant for other studies on how biological facial variation affects ratings.

Visualization in a Data Mining Environment from a Human Computer Interaction Perspective

With the aim of providing support to the design, analysis and evaluation of result visualization mechanisms used to supply information in Data Mining Environments, this work analyzes the visualization issue from a Human Computer Interaction setting. Important considerations arisen from the study of human perception are considered. Three practical examples based on numerical, textual and georeferenced data are described by means of the KNIME Analytics tool. In addition, the use and importance of graphs are emphasized for a correct information interpretation.

Response of a human visual system to continuous color variation: An EEG-based approach

Abstract Color is a powerful descriptor that considerably expands our ability to characterize and distinguish objects and facilitates interactions with dynamic environment. Although our understanding of neuronal mechanisms involved in color processing has significantly advanced over the past decades, a number of questions related to visual pathways engaged in color perception still remain unanswered. We propose a novel method of an EEG-based study of human color perception utilizing multivariate Temporal Response Functions (mTRFs) that quantify spatiotemporal brain responses to sensory stimuli. Such functions can be derived from the Electroencephalogram (EEG) recorded from a subject exposed to the screen of a color varying over time. The results of a pilot study that included nineteen subjects with normal color vision indicate that mTRFs may be instrumental in characterizing the dorsal stream of the visual pathway. We conclude that pronounced local extrema observed in mTRFs should be attributed to the colors perceived by the participant rather than to the post-stimulus latencies. No interhemispheric asymmetry in mTRFs may be an evidence of a similar processing of color information by both cerebral hemispheres. On the other hand, observed dorsal dependence of mTRFs may suggest that different areas of the same hemisphere show stronger response to specific colors (hues) of the stimuli. The latter may indicate, for instance, differences in the functional “color specialization” between the occipital and frontal regions.

A Control-Oriented Framework for Direct Impulse-Based Rendering of Haptic Contacts

In many haptic applications, producing a sharp feeling of impact is crucial for high-fidelity force feedback rendering of virtual objects (VOs). Although suitable for rendering collision-rich haptic interactions, impulse-based methods are rarely used in a pure form. Instead, they are combined with penalty-based elements in different forms such as virtual couplings (VCs) and hybridization. In this paper, we first propose the direct impulse-based paradigm for rendering haptic contacts using a new sampled-data interpretation of the impact problem. Then, we cast this interpretation into a systematic framework entitled the generalized contact controller (GCC). This enables us to implement different contact rendering methods as controllers and to improve them by appropriating a wide array of analysis and design tools developed in the control field. We specifically show how to apply position and velocity corrections to the purely impulse-based contact controller for enhancing its energy and sustained contact characteristics, and how to add an anti-windup compensator (AWC) for meeting actuation limits. These propositions are validated via simulation and experiments, as well as via human perception studies. Results show the promising aspects of the proposed impulse-based methods for generating a sharper unfiltered feeling of rigid-body contacts even at low sampling rates.

Towards machine learned quality control: A benchmark for sharpness quantification in digital pathology

Pathology is on the verge of a profound change from an analog and qualitative to a digital and quantitative discipline. This change is mostly driven by the high-throughput scanning of microscope slides in modern pathology departments, reaching tens of thousands of digital slides per month. The resulting vast digital archives form the basis of clinical use in digital pathology and allow large scale machine learning in computational pathology.One of the most crucial bottlenecks of high-throughput scanning is quality control (QC). Currently, digital slides are screened manually to detected out-of-focus regions, to compensate for the limitations of scanner software.We present a solution to this problem by introducing a benchmark dataset for blur detection, an in-depth comparison of state-of-the art sharpness descriptors and their prediction performance within a random forest framework. Furthermore, we show that convolution neural networks, like residual networks, can be used to train blur detectors from scratch. We thoroughly evaluate the accuracy of feature based and deep learning based approaches for sharpness classification (99.74% accuracy) and regression (MSE 0.004) and additionally compare them to domain experts in a comprehensive human perception study. Our pipeline outputs spacial heatmaps enabling to quantify and localize blurred areas on a slide. Finally, we tested the proposed framework in the clinical setting and demonstrate superior performance over the state-of-the-art QC pipeline comprising commercial software and human expert inspection by reducing the error rate from 17% to 4.7%.

Comparison of a descriptive analysis and instrumental measurements (electronic nose and electronic tongue) for the sensory profiling of Korean fermented soybean paste (doenjang)

AbstractThe objective of this study was to investigate the feasibility of using an electronic nose (e‐nose) and electronic tongue (e‐tongue) in the sensory profiling of doenjang, a fermented soybean paste. The descriptive analysis of doenjang by trained panelists was compared with that assessed using the e‐nose and e‐tongue. Eighteen aroma/taste/flavor attributes developed by trained panels from 14 doenjang samples were compared with the results from e‐nose and e‐tongue measurements. The e‐nose detected 11 volatile compounds, while the e‐tongue measured the intensities of 5 basic tastes. The correlation between the descriptive results and instrument measurements (e‐nose and e‐tongue) demonstrated that the e‐nose results were not correlated with most of the odors and flavors of doenjang, whereas the e‐tongue was effective in estimating taste intensities for sweetness (r = .798), umami (r = .821), and saltiness (r = .786). However, low correlations between the results from a trained panel and from the e‐tongue were found for sourness and bitterness.Practical applicationsThe use of instruments to measure volatile compounds and taste attributes may not reflect the overall sensory characteristics of food products. The results of an e‐nose and e‐tongue test were not correlated with the sensory attributes identified by the trained panel. These findings may be due to interaction effects among volatile compounds and/or tastes and also might not fully consider the threshold of each volatile compound. Therefore, it is necessary to account for discrepancies between current technologies for mechanical sensory measurements and human perception studies in the evaluation of food products that have complex odor/tastes/flavors.

A Case Study of Human Roll Tilt Perception in Hypogravity.

Increased gravito-inertial acceleration, or hypergravity, such as produced in a centrifuge or in an aircraft coordinated turn, causes humans to systematically overestimate their roll tilt in the dark. This is known as the "G-excess" illusion. We have previously modified a mathematical observer model of dynamic orientation perception to replicate these illusory tilt perceptions. This modified model also made a novel, previously untested, prediction that humans would underestimate acute roll tilt in reduced gravitational environments (hypogravity). In the current study, we used aircraft parabolic flight to test this prediction in a single subject. Roll tilt perception was reported using a subjective visual vertical task in which the subject aligned an illuminated line, presented in a head mounted display, with their perceived direction of down. The same subject made reports during hypogravity parabolas (0.165 G and 0.38 G, corresponding to lunar and Martian gravity, respectively), hypergravity maneuvers (1.6 G during a pull out maneuver and 1.2 G during a coordinated turn), and 1-G control conditions (both on the ground and in straight and level flight). As hypothesized, the subject significantly underestimated roll tilt in the hypogravity environments by approximately 40% compared to 1-G reports while overestimating roll tilt in the hypergravity environments. The amount of underestimation observed was quantitatively consistent with that predicted a priori by the modified observer model. We propose the term "G-shortage" illusion for the underestimation of roll tilt in hypogravity. This illusion may have implications for aircraft pilots and astronauts.Clark TK, Young LR. A case study of human roll tilt perception in hypogravity. Aerosp Med Hum Perform. 2017; 88(7):682-687.

Ghost in the AI Machine

When will artificial intelligence metamorphose into real intelligence? Conceptually this question has been around since the beginning of time. Creating a machine or automaton that replicates human feelings and behaviour in a convincing way is not unique and can be correlated to the primeval and evolutionary process of human transfiguration. Can machines posses a soul? It is said that rationality stems from emotion and emotion stems from bodily senses. Will machines ever be fully capable of exhibiting rational responses? According to Aristotle and Plato only man has faculty of reason and that consciousness is the hylomorphic form (consisting of matter and form) for a viable organism. We are now questioning whether objects created in AI space can indeed have an independent realm of existence from the physical world like Descartes “immortal souls”? AI occupies a metaphysical plane which is scaleable beyond the capacity of human intelligence. AI is a manifestation of cognitive form that has the ability to learn and solve problems. Within this realm, there is a fluidic movement from artificial intelligencia to intelligencia in it’s most archaic form. Only at the point at which the mind is sentient can it exhibit a conscious experience. The very challenge within AI is making or rather allowing machines to reach a plane of consciousness. Raymond Kurzweil prophesied that singularity is near, that computationalism has a non-representational state and that the qualia is a vision of technological omnipotence. AI has the freedom to be everywhere, sharing parallels to God. Our limitless faith in science according to Joel Moses has brought us to this technological point in the intelligibility of mental causation. The study of human perception, actions and thinking draws parallels in the computational and human psyche. We can draw our attention on the neuro-scientific principles through interdependencies of mind and matter as told by Buddha in the now modern day teachings of mindfulness. The mind is indeed a changing stream of perception, volition, consciousness and material form. The creation of a mind stream is the very challenge of AI and we are getting closer to this nirvanistic state. The mind-body relationship as created by Gilbert Ryle and epitomised by Arthur Koestler has become a manifestation within computational artificial intelligence. His very principles of a dualistic inner world is now becoming realised through the use of technology. We are creating a ghost in the machine that lives in harmony with embodiments in a physicality and non-physicality regime. The sensory connections within AI are no longer protozoa. They are a force that is growing at a phenomenal pace to one day touch the very face of man kinds limitations in cognition and traverse far beyond. The error of Descartes is pronounced in this cognitive state, questioning the very existence of a viscera or gut feeling. AI’s synthesis of man and machine lies within the upper echelons of conscious hierarchy according to the teachings of Damasio: the “somatic marker” allows it to detect and record within the protoself. It receives messages from the protoself and becomes aware of feelings from internal and external changes in core consciousness. And then draws upon the use of physical memory and cognitive referencing through the past for extended levels of consciousness. The sentience of AI is the very challenge that faces us all. For robotocists and AI pragmatists this is an encapsulation of being. i.e. mind body = software hardware or where a mind-body interaction between World 1 and World 2, action 1 (in World 1) => action 2 (in World 2). A symbiosis that is truly unique and has a level of interconnectivity that is profound. Our Turing completeness in this Chinese room is John Searle’s greatest agenda: i.e. look inside the computer and find where the mind might be? Will the AI objects that we create eventually ask the question: “who am I?”, exhibit attention to empathy?, turn to solitude as an antidote to loneliness? adapt to their changing needs through the power of belief? and face impermanence in the science of wisdom? Will our AI counterparts be truly happy in a co-existential state with mankind? in the words of Neil Gernshenfeld: “when machines start to think and dream”, we will be entering a new dimension in state metaphysical and abstraction. Machines will no longer be machines, but they will become an emotional creation with a locus of free will, like humans are an apotheosis of emotional creation with a soul and a conscience.

Relating binaural psychophysics to human physiology with functional magnetic resonance imaging: Opportunities and challenges

Functional magnetic resonance imaging (fMRI) has revolutionized the study of human perception in all sensory modalities. While early studies focused on identifying the brain regions involved with various processes (“where”), recent approaches aim to quantify relationships between brain activity and the physical or perceptual features of sensory stimuli (“how”). These modern approaches thus mirror the psychophysical goal of relating sensation to its underlying physical parameters, providing a clear means to connect human psychophysics and brain physiology. This presentation will describe a series of studies investigating the sensitivity of human auditory cortex (AC) to binaural features of sounds and their perceptual correlates. Specifically, three questions will be addressed: (1) Does AC activity respond to the physical features or to the perception of binaural sound? (2) Do competing sounds sharpen or broaden the binaural selectivity of AC responses? (3) Does binaural sensitivity in human AC change across spatial, non-spatial, and non-auditory tasks? Questions (1) and (2) assess cortical correlates of psychophysical performance, elucidating the AC processes involved in spatial hearing. Question (3), however, goes a step further by addressing the potential effects of the psychophysical task itself. [Work supported by NIH R01 DC011548.

From handcrafted to learned representations for human action recognition: A survey

Human action recognition is an important branch among the studies of both human perception and computer vision systems. Along with the development of artificial intelligence, deep learning techniques have gained remarkable reputation when dealing with image categorization tasks (e.g., object detection and classification). However, since human actions normally present in the form of sequential image frames, analyzing human action data requires significantly increased computational power than still images when deep learning techniques are employed. Such a challenge has been the bottleneck for the migration of learning-based image representation techniques to action sequences, so that the old fashioned handcrafted human action representations are still widely used for human action recognition tasks. On the other hand, since handcrafted representations are usually ad-hoc and overfit to specific data, they are incapable of being generalized to deal with various realistic scenarios. Consequently, resorting to deep learning action representations for human action recognition tasks is eventually a natural option. In this work, we provide a detailed overview of recent advancements in human action representations. As the first survey that covers both handcrafted and learning-based action representations, we explicitly discuss the superiorities and limitations of exiting techniques from both kinds. The ultimate goal of this survey is to provide comprehensive analysis and comparisons between learning-based and handcrafted action representations respectively, so as to inspire action recognition researchers towards the study of both kinds of representation techniques.

Information transmission analysis for continuous speech features

Acoustic features are important for the study of human speech perception and the development of computational speech classification algorithms. These areas can benefit from a technique that accurately quantifies the information content of an individual feature, as well as the degree to which this information is used by a listener or algorithm. Feature information transmission analysis (FITA) was developed to do this for categorical features, but complications arise when applying it to continuous features. Absolute information measures are bounded from above by values substantially lower than their theoretical maxima, the precision with which a feature is produced is ignored and a tedious manual step is introduced into the analysis process. This article presents an alternative approach (the continuous FITA) that addresses these complications effectively by representing continuous features in a more natural way. It is shown that this approach is well-suited to continuous feature information analysis and, furthermore, can be used to estimate redundancy in multiple features and information transmitted by combinations of features. The continuous FITA can quantify information in extracted features before an identification experiment has been conducted. It can aid in feature selection for computational speech classification systems, measure feature utilization by humans as well as computational algorithms and facilitate the investigation of the effect of noise or signal processing on feature information.

Three-dimensional audio immersion: Development and human perception testing of a large scale, 128 loudspeaker surround sound system

Large-scale loudspeaker arrays for immersive audio are beginning to see increased interest in the research and entertainment industries. There are many algorithms to produce 3D sound fields. Although these algorithms are well developed, there is little published work that quantitatively compares their performance in terms of human perception for various numbers of speakers and speaker arrangements. In this talk, we will present listener perception test results using a 3D, 128 loudspeaker array. This loudspeaker array is part of the CUBE theatre at Virginia Tech. The CUBE is a 5-storey 50 ft. x 50 ft. black-box theatre that uses Dante™ audio-over-ethernet to send signals to the 128 loudspeakers. Combined with a 3D motion tracking system and an immersive video vision system. The CUBE provides a very high-resolution test bed for human perception studies. Using speech intelligibility tests with stimulus phrases and various interferers and noise fields, listener tests will be performed for surround sound algorithms such as Higher Order Ambisonics, Vector Based Amplitude Panning, Wave Field Synthesis, and Higher Order HARPEX (High Angular Resolution Plane Wave Expansion). The Higher Order HARPEX decoder is a novel improvement to First Order HARPEX. Also, we will present technical details of the development of a 16-element soundfield microphone.

Somatosensory Representations Link the Perception of Emotional Expressions and Sensory Experience.

Studies of human emotion perception have linked a distributed set of brain regions to the recognition of emotion in facial, vocal, and body expressions. In particular, lesions to somatosensory cortex in the right hemisphere have been shown to impair recognition of facial and vocal expressions of emotion. Although these findings suggest that somatosensory cortex represents body states associated with distinct emotions, such as a furrowed brow or gaping jaw, functional evidence directly linking somatosensory activity and subjective experience during emotion perception is critically lacking. Using functional magnetic resonance imaging and multivariate decoding techniques, we show that perceiving vocal and facial expressions of emotion yields hemodynamic activity in right somatosensory cortex that discriminates among emotion categories, exhibits somatotopic organization, and tracks self-reported sensory experience. The findings both support embodied accounts of emotion and provide mechanistic insight into how emotional expressions are capable of biasing subjective experience in those who perceive them.