28 research outputs found

    Affective Brain-Computer Interfaces

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    Strategies for effective utilization of training data for machine translation

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    Action compositionality with focus on neurodevelopmental disorders

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    A central question in motor neuroscience is how the Central Nervous System (CNS) would handle flexibility at the effector level, that is, how the brain would solve the problem coined by Nikolai Bernstein as the “degrees of freedom problem”, or the task of controlling a much larger number of degrees of freedom (dofs) that is often needed to produce behavior. Flexibility is a bless and a curse: while it enables the same body to engage in a virtually infinite number of behaviors, the CNS is left with the job of figuring out the right subset of dofs to use and how to control and coordinate these degrees. Similarly, at the level of perception, the CNS seeks to obtain information pertaining to the action and actors involved based on perceived motion of other people’s dofs. This problem is believed to be solved with a particular dimensionality reduction strategy, where action production would consist of tuning only a few parameters that control and coordinate a small number of motor primitives, and action perception would take place by applying grouping processes that would solve the inverse problem, that is to identify the motor primitives and the corresponding tuning parameters used by an actor. These parameters can encode not only information on the action per se, but also higher-order cognitive cues like body language or emotion. This compositional view of action representation has an obvious parallel with language: we can think of primitives as words and cognitive systems (motor, perceptual) as different languages. Little is known, however, about how words/primitives would be formed from low-level signals measured at each dof. Here we introduce the SB-ST method, a bottom-up approach to find full-body postural primitives as a set of key postures, that is, vectors corresponding to key relationships among dofs (such as joint rotations) which we call spatial basis (SB) and second, we impose a parametric model to the spatio-temporal (ST) profiles of each SB vector. We showcase the method by applying SB vectors and ST parameters to study vertical jumps of young adults (YAD) typically developing (TD) children and children with Developmental Coordination Disorder (DCD) obtained with motion capture. We also go over a number of other topics related with compositionality: we introduce a top-down system of tool-use primitives based on kinematic events between body parts and objects. The kinematic basis of these events is inspired by the hand-to-object velocity signature reported by movement psychologists in the 1980’s. We discuss the need for custom-made movement measurement strategies to study action primitives on some target populations, for example infants. Having the right tools to record infant movement would be of help, for example, to research in Autism Spectrum Disorder (ASD) where early sensorimotor abnormalities were shown to be linked to future diagnoses of ASD and the development of the typical social traits ASD is mostly known for. We continue the discussion on infant movement measurement where we present an alternative way of processing movement data by using textual descriptions as re- placements to the actual movement signals observed in infant behavioral trials. We explore the fact that these clinical descriptions are freely available as a byproduct of the diagnosis process itself. A typical/atypical classification experiment shows that, at the level of sentences, traditionally used text features in Natural Language Processing such as term frequencies and TF-IDF computed from unigrams and bigrams can be potentially helpful. In the end, we sketch a conceptual, compositional model of action generation based on exploratory results on the jump data, according to which the presence of disorders would be related not to differences in key postures, but in how they are controlled throughout execution. We next discuss the nature of action and actor information representation by analyzing a second dataset with arm-only data (bi-manual coordination and object manipulations) with more target populations than in the jump dataset: TD and DCD children, YAD and seniors with and without Parkinson’s Disease (PD). Multiple group analyses on dofs coupled with explained variances at SB representations suggest that the cost of representing a task as performed by an actor may be equivalent to the cost of representing the task alone. Plus, group discriminating information appears to be more compressed than task-only discriminating information, and because this compression happens at the top spatial bases, we conjecture that groups may be recognized faster than tasks

    The effects of geometry and dynamics on biological pattern formation

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    This project examines the influence of geometry and dynamics on pattern formation in biological development . Since the work of Turing (1952) it has been known that patterns can form spontaneously given certain relatively simple conditions. The Turing mechanism involved a symmetry-breaking bifurcation from a stable spatially homogeneous state. However the development of patterns in developing organisms does not take place from such simple conditions, biological development causes pattern formation to occur within geometric structures which are complex and the environment is very noisy. This thesis examines the effects of such complexity and noise on pattern formation. The biological situations modelled in this thesis relate to the development of the mammalian cortex. The cortex is a very thin sheet, and there is evolutionary and developmental pressure to utilise cortical space to the maximum. This promotes the formation of spatial superstructures encompassing regions serving different functions. Also cortical development produces two types of pattern, one in the actual physical structure, this is common to much biological pattern formation, but also in terms of patterns of neural response which can be viewed as a feature mapping and is specific to cortical function. We examine the first type of pattern formation within the barrel field of the rat cortex, a geometric superstructure that has the properties of a Voronoi tessellation and apply a dynamical constraint from the observation that the patterns are sparse. We show that these constraints produce a distribution of patterns closer to what is observed than predictions derived from studies in a single domain of perfect circular shape. We also discover a novel effect of geometric alignment of patterns in neighbouring domains, without any physical communication between them, in a wide class of tessellations. This effect is confirmed by analysis of actual images of the subbarrel patterns in the developing rat cortex. The effect of geometry and dynamics of the second type of pattern formation is investigated in the patterns of orientation preference of neuronal response in the visual cortex of certain mammals. Where the domains are sufficiently small so that topological defects (pinwheels) cannot form the behaviour is similar to the reaction-diffusion equations. However, when there are many defects in the region alignment at the boundaries disappears

    Boundaries and Topological Algorithms

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    This thesis develops a model for the topological structure of situations. In this model, the topological structure of space is altered by the presence or absence of boundaries, such as those at the edges of objects. This allows the intuitive meaning of topological concepts such as region connectivity, function continuity, and preservation of topological structure to be modeled using the standard mathematical definitions. The thesis shows that these concepts are important in a wide range of artificial intelligence problems, including low-level vision, high-level vision, natural language semantics, and high-level reasoning

    Vibration, Control and Stability of Dynamical Systems

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    From Preface: This is the fourteenth time when the conference “Dynamical Systems: Theory and Applications” gathers a numerous group of outstanding scientists and engineers, who deal with widely understood problems of theoretical and applied dynamics. Organization of the conference would not have been possible without a great effort of the staff of the Department of Automation, Biomechanics and Mechatronics. The patronage over the conference has been taken by the Committee of Mechanics of the Polish Academy of Sciences and Ministry of Science and Higher Education of Poland. It is a great pleasure that our invitation has been accepted by recording in the history of our conference number of people, including good colleagues and friends as well as a large group of researchers and scientists, who decided to participate in the conference for the first time. With proud and satisfaction we welcomed over 180 persons from 31 countries all over the world. They decided to share the results of their research and many years experiences in a discipline of dynamical systems by submitting many very interesting papers. This year, the DSTA Conference Proceedings were split into three volumes entitled “Dynamical Systems” with respective subtitles: Vibration, Control and Stability of Dynamical Systems; Mathematical and Numerical Aspects of Dynamical System Analysis and Engineering Dynamics and Life Sciences. Additionally, there will be also published two volumes of Springer Proceedings in Mathematics and Statistics entitled “Dynamical Systems in Theoretical Perspective” and “Dynamical Systems in Applications”

    Uncertainty in Artificial Intelligence: Proceedings of the Thirty-Fourth Conference

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