1,601 research outputs found

    UMSL Bulletin 2023-2024

    Get PDF
    The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp

    Neuroimaging investigations of cortical specialisation for different types of semantic knowledge

    Get PDF
    Embodied theories proposed that semantic knowledge is grounded in motor and perceptual experiences. This leads to two questions: (1) whether the neural underpinnings of perception are also necessary for semantic cognition; (2) how do biases towards different sensorimotor experiences cause brain regions to specialise for particular types of semantic information. This thesis tackles these questions in a series of neuroimaging and behavioural investigations. Regarding question 1, strong embodiment theory holds that semantic representation is reenactment of corresponding experiences, and brain regions for perception are necessary for comprehending modality-specific concepts. However, the weak embodiment view argues that reenactment may not be necessary, and areas near to perceiving regions may be sufficient to support semantic representation. In the particular case of motion concepts, lateral occipital temporal cortex (LOTC) has been long identified as an important area, but the roles of its different subregions are still uncertain. Chapter 3 examined how different parts of LOTC reacted to written descriptions of motion and static events, using multiple analysis methods. A series of anterior to posterior sub-regions were analyzed through univariate, multivariate pattern analysis (MVPA), and psychophysical interaction (PPI) analyses. MVPA revealed strongest decoding effects for motion vs. static events in the posterior parts of LOTC, including both visual motion area (V5) and posterior middle temporal gyrus (pMTG). In contrast, only the middle portion of LOTC showed increased activation for motion sentences in univariate analyses. PPI analyses showed increased functional connectivity between posterior LOTC and the multiple demand network for motion events. These findings suggest that posterior LOTC, which overlapped with the motion perception V5 region, is selectively involved in comprehending motion events, while the anterior part of LOTC contributes to general semantic processing. Regarding question 2, the hub-and-spoke theory suggests that anterior temporal lobe (ATL) acts as a hub, using inputs from modality-specific regions to construct multimodal concepts. However, some researchers propose temporal parietal cortex (TPC) as an additional hub, specialised in processing and integrating interaction and contextual information (e.g., for actions and locations). These hypotheses are summarized as the "dual-hub theory" and different aspects of this theory were investigated in in Chapters 4 and 5. Chapter 4 focuses on taxonomic and thematic relations. Taxonomic relations (or categorical relations) occur when two concepts belong to the same category (e.g., ā€˜dogā€™ and ā€˜wolfā€™ are both canines). In contrast, thematic relations (or associative relations) refer to situations that two concepts co-occur in events or scenes (e.g., ā€˜dogā€™ and ā€˜boneā€™), focusing on the interaction or association between concepts. Some studies have indicated ATL specialization for taxonomic relations and TPC specialization for thematic relations, but others have reported inconsistent or even converse results. Thus Chapter 4 first conducted an activation likelihood estimation (ALE) meta-analysis of neuroimaging studies contrasting taxonomic and thematic relations. This found that thematic relations reliably engage action and location processing regions (left pMTG and SMG), while taxonomic relations only showed consistent effects in the right occipital lobe. A primed semantic judgement task was then used to test the dual-hub theoryā€™s prediction that taxonomic relations are heavily reliant on colour and shape knowledge, while thematic relations rely on action and location knowledge. This behavioural experiment revealed that action or location priming facilitated thematic relation processing, but colour and shape did not lead to priming effects for taxonomic relations. This indicates that thematic relations rely more on action and location knowledge, which may explain why the preferentially engage TPC, whereas taxonomic relations are not specifically linked to shape and colour features. This may explain why they did not preferentially engage left ATL. Chapter 5 concentrates on event and object concepts. Previous studies suggest ATL specialization for coding similarity of objectsā€™ semantics, and angular gyrus (AG) specialization for sentence and event structure representation. In addition, in neuroimaging studies, event semantics are usually investigated using complex temporally extended stimuli, unlike than the single-concept stimuli used to investigate object semantics. Thus chapter 5 used representational similarity analysis (RSA), univariate analysis, and PPI analysis to explore neural activation patterns for event and object concepts presented as static images. Bilateral AGs encoded semantic similarity for event concepts, with the left AG also coding object similarity. Bilateral ATLs encoded semantic similarity for object concepts but also for events. Left ATL exhibited stronger coding for events than objects. PPI analysis revealed stronger connections between left ATL and right pMTG, and between right AG and bilateral inferior temporal gyrus (ITG) and middle occipital gyrus, for event concepts compared to object concepts. Consistent with the meta-analysis in chapter 4, the results in chapter 5 support the idea of partial specialization in AG for event semantics but do not support ATL specialization for object semantics. In fact, both the meta-analysis and chapter 5 findings suggest greater ATL involvement in coding objects' associations compared to their similarity. To conclude, the thesis provides support for the idea that perceptual brain regions are engaged in conceptual processing, in the case of motion concepts. It also provides evidence for a specialised role for TPC regions in processing thematic relations (pMTG) and event concepts (AG). There was mixed evidence for specialisation within the ATLs and this remains an important target for future research

    Body perception and brain plasticity in blind and sighted individuals

    Get PDF
    Lack of vision is associated with large-scale brain plasticity. Vision, touch, proprioception, interoception, and other sensory modalities are thought to play a vital role in developing and maintaining bodily awareness. How do blind people perceive their bodies, and what kind of compensatory neuroplasticity processes are involved? This thesis comprises a series of experiments focused on a profoundly understudied topic ā€“ the perception of oneā€™s body following blindness. Study I shows that blind individuals are significantly better at perceiving their heartbeats than sighted individuals. The results indicate that blind individuals experience signals from inner organs differently than sighted individuals, which has implications for further research on emotional processing and bodily awareness. Study II provides a broader insight into tactile perception following blindness by studying discriminative and affective touch plasticity in blind and sighted groups. A key novel finding is changed pleasantness sensation due to affective touch, that is, slow, gentle, caress-like stroking of the skin, especially on the palm, in blind participants compared to sighted participants. The results have implications for understanding social and physical interactions in blind individuals. Study III re-examines a classic paradigm to study multisensory bodily awareness, the somatic rubber hand illusion, in a large sample of blind participants with a well-matched sighted control group. The results present strong evidence that blind individuals are ā€œimmuneā€ to this illusion which suggests that they rely more on unisensory processing rather than multimodal integration of sensory signals, compared to sighted individuals. Study IV investigates the effect of short-term visual deprivation by a two-hour blindfolding procedure on the bodily senses of cardiac interoception, thermosensation, and discriminative touch in sighted participants. The results show no effect on these senses, which suggests that the changes observed in blind individuals on these sensory functions relate to their long-term lack of visual experience and associated brain plasticity changes. Finally, Study V uses structural magnetic resonance imaging to analyze cortical thickness in a group of blind individuals and a matched sighted control group and relate the cortical thickness measure to the behaviorally registered changes in cardiac interoceptive accuracy. The key finding is that blind individuals with thicker occipital cortices are better at sensing their heartbeats; this finding advances our understanding of the limits of cross-modal plasticity following blindness and suggests that the visual cortex supports the awareness of inner bodily sensations in blind individuals. Overall, this thesis is the first systematic characterization of differences and similarities between blind and sighted individuals in body perception and functioning of the bodily senses, opening a line of research with important links to mental health

    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

    Get PDF
    This ļ¬fth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different ļ¬elds of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modiļ¬ed Proportional Conļ¬‚ict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classiļ¬ers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identiļ¬cation of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classiļ¬cation. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classiļ¬cation, and hybrid techniques mixing deep learning with belief functions as well

    On the Utility of Representation Learning Algorithms for Myoelectric Interfacing

    Get PDF
    Electrical activity produced by muscles during voluntary movement is a reflection of the firing patterns of relevant motor neurons and, by extension, the latent motor intent driving the movement. Once transduced via electromyography (EMG) and converted into digital form, this activity can be processed to provide an estimate of the original motor intent and is as such a feasible basis for non-invasive efferent neural interfacing. EMG-based motor intent decoding has so far received the most attention in the field of upper-limb prosthetics, where alternative means of interfacing are scarce and the utility of better control apparent. Whereas myoelectric prostheses have been available since the 1960s, available EMG control interfaces still lag behind the mechanical capabilities of the artificial limbs they are intended to steerā€”a gap at least partially due to limitations in current methods for translating EMG into appropriate motion commands. As the relationship between EMG signals and concurrent effector kinematics is highly non-linear and apparently stochastic, finding ways to accurately extract and combine relevant information from across electrode sites is still an active area of inquiry.This dissertation comprises an introduction and eight papers that explore issues afflicting the status quo of myoelectric decoding and possible solutions, all related through their use of learning algorithms and deep Artificial Neural Network (ANN) models. Paper I presents a Convolutional Neural Network (CNN) for multi-label movement decoding of high-density surface EMG (HD-sEMG) signals. Inspired by the successful use of CNNs in Paper I and the work of others, Paper II presents a method for automatic design of CNN architectures for use in myocontrol. Paper III introduces an ANN architecture with an appertaining training framework from which simultaneous and proportional control emerges. Paper Iv introduce a dataset of HD-sEMG signals for use with learning algorithms. Paper v applies a Recurrent Neural Network (RNN) model to decode finger forces from intramuscular EMG. Paper vI introduces a Transformer model for myoelectric interfacing that do not need additional training data to function with previously unseen users. Paper vII compares the performance of a Long Short-Term Memory (LSTM) network to that of classical pattern recognition algorithms. Lastly, paper vIII describes a framework for synthesizing EMG from multi-articulate gestures intended to reduce training burden

    Soundscape in Urban Forests

    Get PDF
    This Special Issue of Forests explores the role of soundscapes in urban forested areas. It is comprised of 11 papers involving soundscape studies conducted in urban forests from Asia and Africa. This collection contains six research fields: (1) the ecological patterns and processes of forest soundscapes; (2) the boundary effects and perceptual topology; (3) natural soundscapes and human health; (4) the experience of multi-sensory interactions; (5) environmental behavior and cognitive disposition; and (6) soundscape resource management in forests

    Specification of dorsal root ganglia sensory neuron subpopulations derived from human pluripotent stem cells

    Get PDF
    The detection of sensations is essential for everyday functions and requires specialised dorsal root ganglia (DRG) sensory neurons to detect and transmit the stimuli to the central nervous system for processing. The DRG sensory neurons can be broadly classified as either (1) proprioceptors (that detect movement, muscle pressure, and tension), (2) low threshold mechanoreceptors (LTMRs) (that detect touch, hair deflection, and vibration) or (3) nociceptors (that detect pain arising from harmful thermal, mechanical, and chemical stimuli). Unfortunately, there are major challenges in studying sensory perception and disease, including the difficulty in acquiring human tissue samples and the limitations in the translatability of rodent models due to inherent differences between human and rodent sensory neurons. The use of human pluripotent stem cells (hPSCs) can circumvent these challenges by providing a constant source of human cells that can then be differentiated towards sensory neuron cultures. However, current protocols to generate sensory neuron cultures are often limited by low reproducibility, low neuronal yields, mixed populations of neurons, prevalence of nonneuronal cells within the cultures, as well as the requirement of long maturation stages to obtain functionally mature neurons. A promising approach to generate populations of functional sensory neurons is by mimicking sensory neurogenesis using a combined stepwise addition of extrinsic factors (small molecules and growth factors) to direct hPSCs towards progenitor states and neuronal types, combined with the induced expression of lineage-specifying transcription factors to drive the differentiation to a specific neuronal fate. Thus, the major aim of the work described in this thesis was to derive DRG sensory neurons using a combined extrinsic factor and induced transcription factor differentiation approach to generate cultures of sensory neurons and to then functionally characterise the sensory neurons. A key goal of this PhD thesis was to mimic sensory neurogenesis by inducing the expression of lineage specific transcription factors at a developmentally relevant progenitor cell type (i.e., enriched neural crest cells). The work presented in Chapter 3 describes the successful differentiation of hPSCs into caudal neural progenitors (CNPs), which were then further differentiated and enriched for neural crest cells. This protocol was then implemented in Chapters 4 and 5, which aimed to generate and functionally characterise hPSC-derived sensory neurons by inducing the expression of lineage specific transcription factors in the hPSC-derived neural crest cells. The work in Chapter 4 determined that the induced expression of the transcription factors, NEUROGENIN-1 (NGN1) or NEUROGENIN-2 (NGN2), in neural crest cells both significantly enhanced sensory neuron differentiation efficiency and generated a heterogeneous population of functional sensory neurons. The results presented in Chapter 5 demonstrated that the induced co-expression of the lineage specific transcription factors, NGN2 and RUNT RELATED TRANSCRIPTION FACTOR 3 (RUNX3) or NGN2 and SHORT STATURE HOMEOBOX 2 (SHOX2) in hPSC-derived neural crest cells generated enriched mature sensory neuron cultures that had expression and functional profiles consistent with proprioceptors or LTMRs, respectively. Additionally, the work described in Chapter 5 also aimed to investigate whether there are functional differences in the mechanosensory physiology between the two classes of hPSC-derived mechanosensory neurons and the molecular mechanisms by which the two classes of hPSC-derived mechanosensory neurons respond to stimuli. The mechanosensory neurons, denoted as induced-proprioceptor neurons (iPN) and induced-LTMR neurons (iLTMR) were exquisitely sensitive to mechanical stimuli and exhibited distinct mechanically sensitive responses to stretch and to submicrometer (0.1 Ī¼m) mechanical stimulation by probe indentation to the soma. Additionally, the iPN and iLTMR displayed different adaptation kinetics reflective of distinct sensory specialisations. Importantly, the iPN and iLTMR fired action potentials in response to \u3c 1.0 Ī¼m mechanical stimulation (probe indentation) and knockdown experiments demonstrated that these responses to mechanical stimulation were predominately mediated by PIEZO2. Taken together, the work described in this thesis demonstrates the successful generation of heterogenous and enriched populations of functional sensory neurons from hPSCs via the combination of extrinsic factors and induced expression of lineage specific transcription factors. The derived sensory neurons represent excellent models for the study of human sensory neuron development, peripheral neuropathies, mechanosensory physiology and for the development of directed therapies toward these neuronal populations that become compromised by trauma or neurodegenerative conditions

    Imagining & Sensing: Understanding and Extending the Vocalist-Voice Relationship Through Biosignal Feedback

    Get PDF
    The voice is body and instrument. Third-person interpretation of the voice by listeners, vocal teachers, and digital agents is centred largely around audio feedback. For a vocalist, physical feedback from within the body provides an additional interaction. The vocalistā€™s understanding of their multi-sensory experiences is through tacit knowledge of the body. This knowledge is difficult to articulate, yet awareness and control of the body are innate. In the ever-increasing emergence of technology which quantifies or interprets physiological processes, we must remain conscious also of embodiment and human perception of these processes. Focusing on the vocalist-voice relationship, this thesis expands knowledge of human interaction and how technology influences our perception of our bodies. To unite these different perspectives in the vocal context, I draw on mixed methods from cog- nitive science, psychology, music information retrieval, and interactive system design. Objective methods such as vocal audio analysis provide a third-person observation. Subjective practices such as micro-phenomenology capture the experiential, first-person perspectives of the vocalists them- selves. Quantitative-qualitative blend provides details not only on novel interaction, but also an understanding of how technology influences existing understanding of the body. I worked with vocalists to understand how they use their voice through abstract representations, use mental imagery to adapt to altered auditory feedback, and teach fundamental practice to others. Vocalists use multi-modal imagery, for instance understanding physical sensations through auditory sensations. The understanding of the voice exists in a pre-linguistic representation which draws on embodied knowledge and lived experience from outside contexts. I developed a novel vocal interaction method which uses measurement of laryngeal muscular activations through surface electromyography. Biofeedback was presented to vocalists through soni- fication. Acting as an indicator of vocal activity for both conscious and unconscious gestures, this feedback allowed vocalists to explore their movement through sound. This formed new perceptions but also questioned existing understanding of the body. The thesis also uncovers ways in which vocalists are in control and controlled by, work with and against their bodies, and feel as a single entity at times and totally separate entities at others. I conclude this thesis by demonstrating a nuanced account of human interaction and perception of the body through vocal practice, as an example of how technological intervention enables exploration and influence over embodied understanding. This further highlights the need for understanding of the human experience in embodied interaction, rather than solely on digital interpretation, when introducing technology into these relationships
    • ā€¦
    corecore