231 research outputs found

    Change blindness: eradication of gestalt strategies

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    Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

    Continual Lifelong Learning with Neural Networks: A Review

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    Humans and animals have the ability to continually acquire, fine-tune, and transfer knowledge and skills throughout their lifespan. This ability, referred to as lifelong learning, is mediated by a rich set of neurocognitive mechanisms that together contribute to the development and specialization of our sensorimotor skills as well as to long-term memory consolidation and retrieval. Consequently, lifelong learning capabilities are crucial for autonomous agents interacting in the real world and processing continuous streams of information. However, lifelong learning remains a long-standing challenge for machine learning and neural network models since the continual acquisition of incrementally available information from non-stationary data distributions generally leads to catastrophic forgetting or interference. This limitation represents a major drawback for state-of-the-art deep neural network models that typically learn representations from stationary batches of training data, thus without accounting for situations in which information becomes incrementally available over time. In this review, we critically summarize the main challenges linked to lifelong learning for artificial learning systems and compare existing neural network approaches that alleviate, to different extents, catastrophic forgetting. We discuss well-established and emerging research motivated by lifelong learning factors in biological systems such as structural plasticity, memory replay, curriculum and transfer learning, intrinsic motivation, and multisensory integration

    Swayed by sound: sonic guidance as a neurorehabilitation strategy in the cerebellar ataxias

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    Cerebellar disease leads to problems in controlling movement. The most common difficulties are dysmetria and instability when standing. Recent understanding of cerebellar function has expanded to include non -motor aspects such as emotional, cognitive and sensory processing. Deficits in the acquisition and processing of sensory information are one explanation for the movement problems observed in cerebellar ataxia. Sensory deficits result in an inability to make predictions about future events; a primary function of the cerebellum. A question therefore, is whether augmenting or replacing sensory information can improve motor performance in cerebellar disease. This question is tested in this thesis by augmenting sensory information through the provision of an auditory movement guide.A variable described in motor control theory (tau) was used to develop auditory guides that were continuous and dynamic. A reaching experiment using healthy individuals showed that the timing of peak velocity, audiomotor coordination accuracy, and velocity of approach, could be altered in line with the movement parameters embedded in the auditory guides. The thesis then investigated the use of these sonic guides in a clinical population with cerebellar disease. Performance on neurorehabilitation exercises for balance control was tested in twenty people with cerebellar atrophy, with and without auditory guides. Results suggested that continuous, predictive, dynamic auditory guidance is an effective way of improving iii movement smoothness in ataxia (as measured by jerk). In addition, generating and swaying with imaginary auditory guides was also found to increase movement smoothness in cerebellar disease.Following the tests of instantaneous effects, the thesis then investigated the longterm consequences on motor behaviour of following a two -month exercise with auditory guide programme. Seven people with cerebellar atrophy were assessed pre - and post -intervention using two measures, weight -shifting and walking. The results of the weight -shifting test indicated that the sonic -guide exercise programme does not initiate long -term changes in motor behaviour. Whilst there were minor, improvements in walking, because of the weight -shifting results, these could not be attributed to the sonic guides. This finding confirms the difficulties of motor rehabilitation in people with cerebellar disease.This thesis contributes original findings to the field of neurorehabilitation by first showing that on -going and predictive stimuli are an appropriate tool for improving motor behaviour. In addition, the thesis is the first of its kind to apply externally presented guides that convey continuous meaningful information within a clinical population. Finally, findings show that sensory augmentation using the auditory domain is an effective way of improving motor coordination in some forms of cerebellar disease

    Cortico-spinal modularity in the parieto-frontal system: a new perspective on action control

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    : Classical neurophysiology suggests that the motor cortex (MI) has a unique role in action control. In contrast, this review presents evidence for multiple parieto-frontal spinal command modules that can bypass MI. Five observations support this modular perspective: (i) the statistics of cortical connectivity demonstrate functionally-related clusters of cortical areas, defining functional modules in the premotor, cingulate, and parietal cortices; (ii) different corticospinal pathways originate from the above areas, each with a distinct range of conduction velocities; (iii) the activation time of each module varies depending on task, and different modules can be activated simultaneously; (iv) a modular architecture with direct motor output is faster and less metabolically expensive than an architecture that relies on MI, given the slow connections between MI and other cortical areas; (v) lesions of the areas composing parieto-frontal modules have different effects from lesions of MI. Here we provide examples of six cortico-spinal modules and functions they subserve: module 1) arm reaching, tool use and object construction; module 2) spatial navigation and locomotion; module 3) grasping and observation of hand and mouth actions; module 4) action initiation, motor sequences, time encoding; module 5) conditional motor association and learning, action plan switching and action inhibition; module 6) planning defensive actions. These modules can serve as a library of tools to be recombined when faced with novel tasks, and MI might serve as a recombinatory hub. In conclusion, the availability of locally-stored information and multiple outflow paths supports the physiological plausibility of the proposed modular perspective

    Sensor Fusion in the Perception of Self-Motion

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    This dissertation has been written at the Max Planck Institute for Biological Cybernetics (Max-Planck-Institut für Biologische Kybernetik) in Tübingen in the department of Prof. Dr. Heinrich H. Bülthoff. The work has universitary support by Prof. Dr. Günther Palm (University of Ulm, Abteilung Neuroinformatik). Main evaluators are Prof. Dr. Günther Palm, Prof. Dr. Wolfgang Becker (University of Ulm, Sektion Neurophysiologie) and Prof. Dr. Heinrich Bülthoff.amp;lt;bramp;gt;amp;lt;bramp;gt; The goal of this thesis was to investigate the integration of different sensory modalities in the perception of self-motion, by using psychophysical methods. Experiments with healthy human participants were to be designed for and performed in the Motion Lab, which is equipped with a simulator platform and projection screen. Results from psychophysical experiments should be used to refine models of the multisensory integration process, with an mphasis on Bayesian (maximum likelihood) integration mechanisms.amp;lt;bramp;gt;amp;lt;bramp;gt; To put the psychophysical experiments into the larger framework of research on multisensory integration in the brain, results of neuroanatomical and neurophysiological experiments on multisensory integration are also reviewed

    27th Annual Computational Neuroscience Meeting (CNS*2018): Part One

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    Applying the Free-Energy Principle to Complex Adaptive Systems

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    The free energy principle is a mathematical theory of the behaviour of self-organising systems that originally gained prominence as a unified model of the brain. Since then, the theory has been applied to a plethora of biological phenomena, extending from single-celled and multicellular organisms through to niche construction and human culture, and even the emergence of life itself. The free energy principle tells us that perception and action operate synergistically to minimize an organism’s exposure to surprising biological states, which are more likely to lead to decay. A key corollary of this hypothesis is active inference—the idea that all behavior involves the selective sampling of sensory data so that we experience what we expect to (in order to avoid surprises). Simply put, we act upon the world to fulfill our expectations. It is now widely recognized that the implications of the free energy principle for our understanding of the human mind and behavior are far-reaching and profound. To date, however, its capacity to extend beyond our brain—to more generally explain living and other complex adaptive systems—has only just begun to be explored. The aim of this collection is to showcase the breadth of the free energy principle as a unified theory of complex adaptive systems—conscious, social, living, or not
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