Context sensitivity in action decreases along the autism spectrum: a predictive processing perspective

Recent predictive processing accounts of perception and action point towards a key challenge for the nervous system in dynamically optimizing the balance between incoming sensory information and existing expectations regarding the state of the environment. Here, we report differences in the influence of the preceding sensory context on motor function, varying with respect to both clinical and subclinical features of autism spectrum disorder (ASD). Reach-to-grasp movements were recorded subsequent to an inactive period in which illusory ownership of a prosthetic limb was induced. We analysed the sub-components of reach trajectories derived using a minimum-jerk fitting procedure. Non-clinical adults low in autistic features showed disrupted movement execution following the illusion compared to a control condition. By contrast, individuals higher in autistic features (both those with ASD and non-clinical individuals high in autistic traits) showed reduced sensitivity to the presence of the illusion in their reaching movements while still exhibiting the typical perceptual effects of the illusion. Clinical individuals were distinct from non-clinical individuals scoring high in autistic features, however, in the early stages of movement. These results suggest that the influence of high-level representations of the environment differs between individuals, contributing to clinical and subclinical differences in motor performance that manifest in a contextual manner. As high-level representations of context help to explain fluctuations in sensory input over relatively longer time scales, more circumscribed sensitivity to prior or contextual information in autistic sensory processing could contribute more generally to reduced social comprehension, sensory impairments and a stronger desire for predictability and routine.

Optimisation of nonlinear motion cueing algorithm based on genetic algorithm

Motion cueing algorithms (MCAs) are playing a significant role in driving simulators, aiming to deliver the most accurate human sensation to the simulator drivers compared with a real vehicle driver, without exceeding the physical limitations of the simulator. This paper provides the optimisation design of an MCA for a vehicle simulator, in order to find the most suitable washout algorithm parameters, while respecting all motion platform physical limitations, and minimising human perception error between real and simulator driver. One of the main limitations of the classical washout filters is that it is attuned by the worst-case scenario tuning method. This is based on trial and error, and is effected by driving and programmers experience, making this the most significant obstacle to full motion platform utilisation. This leads to inflexibility of the structure, production of false cues and makes the resulting simulator fail to suit all circumstances. In addition, the classical method does not take minimisation of human perception error and physical constraints into account. Production of motion cues and the impact of different parameters of classical washout filters on motion cues remain inaccessible for designers for this reason. The aim of this paper is to provide an optimisation method for tuning the MCA parameters, based on nonlinear filtering and genetic algorithms. This is done by taking vestibular sensation error into account between real and simulated cases, as well as main dynamic limitations, tilt coordination and correlation coefficient. Three additional compensatory linear blocks are integrated into the MCA, to be tuned in order to modify the performance of the filters successfully. The proposed optimised MCA is implemented in MATLAB/Simulink software packages. The results generated using the proposed method show increased performance in terms of human sensation, reference shape tracking and exploiting the platform more efficiently without reaching the motion limitations.

The gainers

Performed over 3 nights, The Gainers is an exploration of object-led creative practice within a psychophysical performance approach. Exploring Gibbs (2005) proposition that places the body as central to perception, the research questioned the relationship between object, task and movement when devising and investigated how the inherent structure within each purpose (object’s purpose, the purpose of the task, and purposeful movement) interacted to support greater divergence within the creative work, and similarly acted to provide additional coherence in convergent stages. Perception, Gibbs claims, ‘is not something that only occurs through specific sensory apparatus (e.g. eyeballs and visual system) in conjunction with particular brain areas, but is a kinesthetic activity that includes all aspects of the body in action’ (12). The research, through practice, found that solo bodied are cohered around shared task and object purposes bringing a shared embodied vocabulary to the ensemble and enhancing the way the actor/s invest meaning between their bodies. Just one outcome from The Charlie Project in which the forms of Charlie Chaplin provide the context and are investigated as structures for inter-textual performativity and design led performance making, The Gainers was developed in February-June 2015, and played to three general public audiences: 3, 4, 5 June.

Incorporating human perception with the motion washout filter using fuzzy logic control

Abstract—Nowadays, classical washout filters are extensively used in commercial motion simulators. Even though there are several advantages for classical washout filters, such as short processing time, simplicity and ease of adjustment, they have several shortcomings. The main disadvantage is the fixed scheme and parameters of the classical washout filter cause inflexibility of the structure and thus the resulting simulator fails to suit all circumstances. Moreover, it is a conservative approach and the platform cannot be fully exploited. The aim of this research is to present a fuzzy logic approach and take the human perception error into account in the classical motion cueing algorithm, in order to improve both the physical limits of restitution and realistic human sensations. The fuzzy compensator signal is applied to adjust the filtered signals on the longitudinal and rotational channels online, as well as the tilt coordination to minimize the vestibular sensation error below the human perception threshold. The results indicate that the proposed fuzzy logic controllers significantly minimize the drawbacks of having fixed parameters and conservativeness in the classical washout filter. In addition, the performance of motion cueing algorithm and human perception for most occasions is improved.

Human perception-based washout filtering using genetic algorithm

The Motion Cueing Algorithm (MCA) transforms longitudinal and rotational motions into simulator movement, aiming to regenerate high fidelity motion within the simulators physical limitations. Classical washout filters are widely used in commercial simulators because of their relative simplicity and reasonable performance. The main drawback of classical washout filters is the inappropriate empirical parameter tuning method that is based on trial-and-error, and is effected by programmers’ experience. This is the most important obstacle to exploiting the platform efficiently. Consequently, the conservative motion produces false cue motions. Lack of consideration for human perception error is another deficiency of classical washout filters and also there is difficulty in understanding the effect of classical washout filter parameters on generated motion cues. The aim of this study is to present an effortless optimization method for adjusting the classical MCA parameters, based on the Genetic Algorithm (GA) for a vehicle simulator in order to minimize human sensation error between the real and simulator driver while exploiting the platform within its physical limitations. The vestibular sensation error between the real and simulator driver as well as motion limitations have been taken into account during optimization. The proposed optimized MCA based on GA is implemented in MATLAB/Simulink. The results show the superiority of the proposed MCA as it improved the human sensation, maximized reference signal shape following and exploited the platform more efficiently within the motion constraints.

Robot coordination for energy-balanced matching and sequence dispatch of robots to events

Given a set of events and a set of robots, the dispatch problem is to allocate one robot for each event to visit it. In a single round, each robot may be allowed to visit only one event (matching dispatch), or several events in a sequence (sequence dispatch). In a distributed setting, each event is discovered by a sensor and reported to a robot. Here, we present novel algorithms aimed at overcoming the shortcomings of several existing solutions. We propose pairwise distance based matching algorithm (PDM) to eliminate long edges by pairwise exchanges between matching pairs. Our sequence dispatch algorithm (SQD) iteratively finds the closest event-robot pair, includes the event in dispatch schedule of the selected robot and updates its position accordingly. When event-robot distances are multiplied by robot resistance (inverse of the remaining energy), the corresponding energy-balanced variants are obtained. We also present generalizations which handle multiple visits and timing constraints. Our localized algorithm MAD is based on information mesh infrastructure and local auctions within the robot network for obtaining the optimal dispatch schedule for each robot. The simulations conducted confirm the advantages of our algorithms over other existing solutions in terms of average robot-event distance and lifetime.

Taming the wild elephant : yoga, cognition and emotion

Yoga tradition suggests that the nature of being is awarenes - being aware of the effects of thoughts and feelings, beliefs and emotions. Yoga Philosophy appreciates the life-effects of perception. Yoga promotes a way of being that ultimately transcends basic thoughts and wants, moving beyond, to a state of observer awareness - something the Indian sage Patanjali describes as the process of apperception, where the perceiver is aware of the act of perceiving. This paper looks at the complex relationship between an individual's wellbeing, cognitive processes and emotional life. It explores the principles of mindfulness as a vehicle for emotional balance and investigates the link between Yoga, cognition and emotion. It looks at the physiological influence of cognition and emotion and critiques Yogic philosophy alongside Western cognitive-emotive theories such as Erich Fromm's 'art of being' and the insights presented in Robert C. Solomon's various works on emotional life. This paper also explores the work of other theorists, such as; Patanjali, Aristotle, Georg Feuerstein, Jiddu Krishnamurti, Purushottama Bilimoria and others.

Joint action and the expression of shared intentions: an expanded Taylorian account

After having identified several shortcomings of the so-called 'standard accounts' of shared intentions, this paper will develop a novel framework for understanding such intentions. The framework to be advanced hinges on a notion of ‘expression’, as well as on the claim that shared intentions are expressed—that is, manifested, grasped, shaped and clarified—throughout the unfolding of the joint actions they animate, as well as in the various expressive activities and behaviours that accompany joint action. This claim will be defended with particular reference to the work of Charles Taylor on expression, as well as recent work on embodied cognition.