Behavioral dynamics of steering, obstacle avoidance, and route selection

Identifying factors that contribute to collision avoidance behaviours while walking in a natural environment

Busy walking paths, like in a park, city centre, or shopping mall, frequently necessitate collision avoidance behaviour. Lab-based research has shown how different situation- and person-specific factors, typically studied independently, affect avoidance behaviour. What happens in the real world is unclear. Thus, we filmed unscripted pedestrian walking behaviours on a busy urban path. We leveraged deep learning algorithms to identify and extract pedestrian walking trajectories and had unbiased raters characterize situations where two pedestrians approached each other from opposite ends. We found that smaller medial-lateral distance between approaching pedestrians and smaller crowd size predicted an increased likelihood of a subsequent path deviation. Furthermore, we found that whether a pedestrian looked distracted or held, pushed, or pulled an object predicted medial-lateral distance between pedestrians at time of crossing. Our results highlight both similarities and differences with lab-based behaviour and offer insights relevant to developing accurate computational models for realistic pedestrian movement.

How the Complexity of Psychological Processes Reframes the Issue of Reproducibility in Psychological Science

In the past decade, various recommendations have been published to enhance the methodological rigor and publication standards in psychological science. However, adhering to these recommendations may have limited impact on the reproducibility of causal effects as long as psychological phenomena continue to be viewed as decomposable into separate and additive statistical structures of causal relationships. In this article, we show that (a) psychological phenomena are patterns emerging from nondecomposable and nonisolable complex processes that obey idiosyncratic nonlinear dynamics, (b) these processual features jeopardize the chances of standard reproducibility of statistical results, and (c) these features call on researchers to reconsider what can and should be reproduced, that is, the psychological processes per se, and the signatures of their complexity and dynamics. Accordingly, we argue for a greater consideration of process causality of psychological phenomena reflected by key properties of complex dynamical systems (CDSs). This implies developing and testing formal models of psychological dynamics, which can be implemented by computer simulation. The scope of the CDS paradigm and its convergences with other paradigms are discussed regarding the reproducibility issue. Ironically, the CDS approach could account for both reproducibility and nonreproducibility of the statistical effects usually sought in mainstream psychological science.

A model of task-level human stepping regulation yields semistable walking

A simple lateral dynamic walker, with swing leg dynamics and three adjustable input parameters, is used to study how motor regulation affects frontal-plane stepping. Motivated by experimental observations and phenomenological models, we imposed task-level multi-objective regulation targeting the walker's optimal lateral foot placement at each step. The regulator prioritizes achieving step width and lateral body position goals to varying degrees by choosing a mixture parameter. Our model thus integrates a lateral mechanical template, which captures the fundamental mechanics of frontal-plane walking, with a lateral motor regulation template, an empirically verified model of how humans manipulate lateral foot placements in a goal-directed manner. The model captures experimentally observed stepping fluctuation statistics and demonstrates how linear empirical models of stepping dynamics can emerge from first-principles nonlinear mechanics. We find that task-level regulation gives rise to a goal-equivalent manifold in the system's extended state space of mechanical states and inputs, a subset of which contains a continuum of period-1 gaits forming a semistable set: perturbations off of any of its gaits result in transients that return to the set, though typically to different gaits.

Modelling human navigation and decision dynamics in a first-person herding task

This study investigated whether dynamical perceptual-motor primitives (DPMPs) could also be used to capture human navigation in a first-person herding task. To achieve this aim, human participants played a first-person herding game, in which they were required to corral virtual cows, called targets, into a specified containment zone. In addition to recording and modelling participants' movement trajectories during gameplay, participants' target-selection decisions (i.e. the order in which participants corralled targets) were recorded and modelled. The results revealed that a simple DPMP navigation model could effectively reproduce the movement trajectories of participants and that almost 80% of the participants' target-selection decisions could be captured by a simple heuristic policy. Importantly, when this policy was coupled to the DPMP navigation model, the resulting system could successfully simulate and predict the behavioural dynamics (movement trajectories and target-selection decisions) of participants in novel multi-target contexts. Implications of the findings for understanding complex human perceptual-motor behaviour and the development of artificial agents for robust human-machine interaction are discussed.

Risk of pedestrian collision for persons with peripheral field loss: A computational analysis

SIGNIFICANCE

People with peripheral field loss report colliding with other pedestrians on their blind side(s). We show that, in dyadic collision scenarios between persons, one with field loss, such as homonymous hemianopia, and the other normally sighted pedestrian, collisions occur only if the persons with homonymous hemianopia are overtaking the pedestrians, and the collision risk is concentrated at farther bearing angles than previously suggested.

PURPOSE

Prior work computed the risk of collision while simulating both pedestrians as points and did not consider the ability of the other pedestrian's normal vision to avoid the collision. We extended the model to better characterize the open space collision risk posed for persons with homonymous hemianopia by normally sighted pedestrians where both have volume.

METHODS

We computed the risk of collision with approaching pedestrians using a model that simulates approaching pedestrians as volumetric entities without vision, volumetric entities with vision, and as points for comparison with the prior work. Collision risk of approaching pedestrians is characterized for all three conditions through spatial collision risk maps and collision risk densities as a function of bearing and radial distances.

RESULTS

The collision risk for volumetric pedestrians is slightly different from that of point pedestrians. For volumetric pedestrians simulated with normal vision, the risk of collision was reduced substantially, as the other pedestrians could detect and avoid most impending collisions. The remaining collision risk is from pedestrians approaching at higher bearing angles (>50°) and from shorter radial distances (<2 m). Thus, collisions occurred when the pedestrians started in front of the person with homonymous hemianopia that was overtaking the pedestrian.

CONCLUSIONS

The probability of collisions between pedestrians and the person with peripheral field loss is low and occurs only when the person with peripheral field loss is walking from behind the pedestrian at faster speed, thereby overtaking them. Such collisions occur with pedestrians at higher bearing angles, which should be monitored by assistive aids to avoid collisions. The same collision risk applies not only in homonymous hemianopia but also in other peripheral field loss such as monocular vision loss or concentric field loss, as common in retinitis pigmentosa and glaucoma.

Context-dependence of deterministic and nondeterministic contributions to closed-loop steering control

In natural circumstances, sensory systems operate in a closed loop with motor output, whereby actions shape subsequent sensory experiences. A prime example of this is the sensorimotor processing required to align one's direction of travel, or heading, with one's goal, a behavior we refer to as steering. In steering, motor outputs work to eliminate errors between the direction of heading and the goal, modifying subsequent errors in the process. The closed-loop nature of the behavior makes it challenging to determine how deterministic and nondeterministic processes contribute to behavior. We overcome this by applying a nonparametric, linear kernel-based analysis to behavioral data of monkeys steering through a virtual environment in two experimental contexts. In a given context, the results were consistent with previous work that described the transformation as a second-order linear system. Classically, the parameters of such second-order models are associated with physical properties of the limb such as viscosity and stiffness that are commonly assumed to be approximately constant. By contrast, we found that the fit kernels differed strongly across tasks in these and other parameters, suggesting context-dependent changes in neural and biomechanical processes. We additionally fit residuals to a simple noise model and found that the form of the noise was highly conserved across both contexts and animals. Strikingly, the fitted noise also closely matched that found previously in a human steering task. Altogether, this work presents a kernel-based analysis that characterizes the context-dependence of deterministic and non-deterministic components of a closed-loop sensorimotor task.

A model of task-level human stepping regulation yields semistable walking

A simple lateral dynamic walker, with swing leg dynamics and three adjustable input parameters, is used to study how motor regulation affects frontal plane stepping. Motivated by experimental observations and phenomenological models, we imposed task-level multiobjective regulation targeting the walker's optimal lateral foot placement at each step. The regulator prioritizes achieving step width and lateral body position goals to varying degrees by choosing a mixture parameter. Our model thus integrates a lateral mechanical template, which captures fundamental mechanics of frontal-plane walking, with a lateral motor regulation template, an empirically verified model of how humans manipulate lateral foot placements in a goal-directed manner. The model captures experimentally observed stepping fluctuation statistics and demonstrates how linear empirical models of stepping dynamics can emerge from first-principles nonlinear mechanics. We find that task-level regulation gives rise to a goal equivalent manifold in the system's extended state space of mechanical states and inputs, a subset of which contains a continuum of period-1 gaits forming a semistable set: perturbations off of any of its gaits result in transients that return to the set, though typically to different gaits.

Exploring the challenges of avoiding collisions with virtual pedestrians using a dual-task paradigm in individuals with chronic moderate to severe traumatic brain injury

BACKGROUND

Individuals with a moderate-to-severe traumatic brain injury (m/sTBI), despite experiencing good locomotor recovery six months post-injury, face challenges in adapting their locomotion to the environment. They also present with altered cognitive functions, which may impact dual-task walking abilities. Whether they present collision avoidance strategies with moving pedestrians that are altered under dual-task conditions, however, remains unclear. This study aimed to compare between individuals with m/sTBI and age-matched control individuals: (1), the locomotor and cognitive costs associated with the concurrent performance of circumventing approaching virtual pedestrians (VRPs) while attending to an auditory-based cognitive task and; (2) gaze behaviour associated with the VRP circumvention task in single and dual-task conditions.

METHODOLOGY

Twelve individuals with m/sTBI (age = 43.3 ± 9.5 yrs; >6 mo. post injury) and 12 healthy controls (CTLs) (age = 41.8 ± 8.3 yrs) were assessed while walking in a virtual subway station viewed in a head-mounted display. They performed a collision avoidance task with VRPs, as well as auditory-based cognitive tasks (pitch discrimination and auditory Stroop), both under single and dual-task conditions. Dual-task cost (DTC) for onset distance of trajectory deviation, minimum distance from the VRP, maximum lateral deviation, walking speed, gaze fixations and cognitive task accuracy were contrasted between groups using generalized estimating equations.

RESULTS

In contrast to CTLs who showed locomotor DTCs only, individuals with m/sTBI displayed both locomotor and cognitive DTCs. While both groups walked slower under dual-task conditions, only individuals with m/sTBI failed to modify their onset distance of trajectory deviation and maintained smaller minimum distances and smaller maximum lateral deviation compared to single-task walking. Both groups showed shorter gaze fixations on the approaching VRP under dual-task conditions, but this reduction was less pronounced in the individuals with m/sTBI. A reduction in cognitive task accuracy under dual-task conditions was found in the m/sTBI group only.

CONCLUSION

Individuals with m/sTBI present altered locomotor and gaze behaviours, as well as altered cognitive performances, when executing a collision avoidance task involving moving pedestrians in dual-task conditions. Potential mechanisms explaining those alterations are discussed. Present findings highlight the compromised complex walking abilities in individuals with m/sTBI who otherwise present a good locomotor recovery.

Evidence for Shifting Cognitive Strategies when Icons Appear in Unexpected Locations

OBJECTIVE

The present study examines the cognitive effects of placing icons in unexpected spatial locations within websites.

BACKGROUND

Prior research has revealed evidence for cognitive conflict when web icons occur in unexpected locations (e.g., cart, top left), generally consistent with a dynamical systems models. Here, we compare the relative strength of evidence for both dual and dynamical systems models.

METHODS

Participants clicked on icons located in either expected (e.g., cart, top right) or unexpected (e.g., cart, top left) locations while mouse trajectories were continuously recorded. Trajectories were classified according to prototypes associated with each cognitive model. The dynamical systems model predicts curved trajectories, while the dual-systems model predicts straight and change of mind trajectories.

RESULTS

Trajectory classification revealed that curved trajectories increased (+11%), while straight and change of mind trajectories decreased (-12%) when target icons occurred in unexpected locations (p < .001).

CONCLUSION

Rather than employing a single cognitive strategy, users shift from a primarily dual-systems to dynamical systems strategy when icons occur in unexpected locations.

APPLICATION

Potential applications of this work include the assessment of cognitive impacts such as mental workload and cognitive conflict during real-time interaction with websites and other screen-based interfaces, personalization and adaptive interfaces based on an individual's cognitive strategy, and data-driven A/B testing of alternative interface designs.

Human Crowds as Social Networks: Collective Dynamics of Consensus and Polarization

A ubiquitous type of collective behavior and decision-making is the coordinated motion of bird flocks, fish schools, and human crowds. Collective decisions to move in the same direction, turn right or left, or split into subgroups arise in a self-organized fashion from local interactions between individuals without central plans or designated leaders. Strikingly similar phenomena of consensus (collective motion), clustering (subgroup formation), and bipolarization (splitting into extreme groups) are also observed in opinion formation. As we developed models of crowd dynamics and analyzed crowd networks, we found ourselves going down the same path as models of opinion dynamics in social networks. In this article, we draw out the parallels between human crowds and social networks. We show that models of crowd dynamics and opinion dynamics have a similar mathematical form and generate analogous phenomena in multiagent simulations. We suggest that they can be unified by a common collective dynamics, which may be extended to other psychological collectives. Models of collective dynamics thus offer a means to account for collective behavior and collective decisions without appealing to a priori mental structures.

Measuring skill via player dynamics in football dribbling

Although a myriad of studies have been conducted on player behavior in football, in-depth studies with structured theory are rare due to the difficulty in quantifying individual player skills and team strategies. We propose a physics-based mathematical model that describes football players' movements during dribbling situations, parameterized by the attacker aggressiveness, the defender hesitance and the top speed of both players. These player- and situation-specific parameters are extracted by fitting the model to real player trajectories from Major League Soccer games, and enable the quantification of player dribbling attributes and decisions beyond classical statistics. We show that the model captures the essential dribbling dynamics, and analyze how differences between parameters in varying game situations provide valuable insights into players' behavior. Lastly, we quantitatively study how changes in the player's parameters impact dribbling performance, enabling the model to provide scientific guidance to player training, scouting and game strategy development.

Adaptive Optimization Algorithm for Resetting Techniques in Obstacle-Ridden Environments

Redirected Walking (RDW) algorithms aim to impose several types of gains on users immersed in Virtual Reality and distort their walking paths in the real world, thus enabling them to explore a larger space. Since collision with physical boundaries is inevitable, a reset strategy needs to be provided to allow users to reset when they hit the boundary. However, most reset strategies are based on simple heuristics by choosing a seemingly suitable solution, which may not perform well in practice. In this article, we propose a novel optimization-based reset algorithm adaptive to different RDW algorithms. Inspired by the approach of finite element analysis, our algorithm splits the boundary of the physical world by a set of endpoints. Each endpoint is assigned a reset vector to represent the optimized reset direction when hitting the boundary. The reset vectors on the edge will be determined by the interpolation between two neighbouring endpoints. We conduct simulation-based experiments for three RDW algorithms with commonly used reset algorithms to compare with. The results demonstrate that the proposed algorithm significantly reduces the number of resets.

Slipping while counting: gaze-gait interactions during perturbed walking under dual-task conditions

Walking is a complex task. To prevent falls and injuries, gait needs to constantly adjust to the environment. This requires information from various sensory systems; in turn, moving through the environment continuously changes available sensory information. Visual information is available from a distance, and therefore most critical when negotiating difficult terrain. To effectively sample visual information, humans adjust their gaze to the terrain or-in laboratory settings-when facing motor perturbations. During activities of daily living, however, only a fraction of sensory and cognitive resources can be devoted to ensuring safe gait. How do humans deal with challenging walking conditions when they face high cognitive load? Young, healthy participants (N = 24) walked on a treadmill through a virtual, but naturalistic environment. Occasionally, their gait was experimentally perturbed, inducing slipping. We varied cognitive load by asking participants in some blocks to count backward in steps of seven; orthogonally, we varied whether visual cues indicated upcoming perturbations. We replicated earlier findings on how humans adjust their gaze and their gait rapidly and flexibly on various time scales: eye and head movements responded in a partially compensatory pattern and visual cues mostly affected eye movements. Interestingly, the cognitive task affected mainly head orientation. During the cognitive task, we found no clear signs of a less stable gait or of a cautious gait mode, but evidence that participants adapted their gait less to the perturbations than without secondary task. In sum, cognitive load affects head orientation and impairs the ability to adjust to gait perturbations.

Unfreezing autonomous vehicles with game theory, proxemics, and trust

Recent years have witnessed the rapid deployment of robotic systems in public places such as roads, pavements, workplaces and care homes. Robot navigation in environments with static objects is largely solved, but navigating around humans in dynamic environments remains an active research question for autonomous vehicles (AVs). To navigate in human social spaces, self-driving cars and other robots must also show social intelligence. This involves predicting and planning around pedestrians, understanding their personal space, and establishing trust with them. Most current AVs, for legal and safety reasons, consider pedestrians to be obstacles, so these AVs always stop for or replan to drive around them. But this highly safe nature may lead pedestrians to take advantage over them and slow their progress, even to a complete halt. We provide a review of our recent research on predicting and controlling human–AV interactions, which combines game theory, proxemics and trust, and unifies these fields via quantitative, probabilistic models and robot controllers, to solve this “freezing robot” problem.

Multi-scopic neuro-cognitive adaptation for legged locomotion robots

Dynamic locomotion is realized through a simultaneous integration of adaptability and optimality. This article proposes a neuro-cognitive model for a multi-legged locomotion robot that can seamlessly integrate multi-modal sensing, ecological perception, and cognition through the coordination of interoceptive and exteroceptive sensory information. Importantly, cognitive models can be discussed as micro-, meso-, and macro-scopic; these concepts correspond to sensing, perception, and cognition; and short-, medium-, and long-term adaptation (in terms of ecological psychology). The proposed neuro-cognitive model integrates these intelligent functions from a multi-scopic point of view. Macroscopic-level presents an attention mechanism with short-term adaptive locomotion control conducted by a lower-level sensorimotor coordination-based model. Macrosopic-level serves environmental cognitive map featuring higher-level behavior planning. Mesoscopic level shows integration between the microscopic and macroscopic approaches, enabling the model to reconstruct a map and conduct localization using bottom-up facial environmental information and top-down map information, generating intention towards the ultimate goal at the macroscopic level. The experiments demonstrated that adaptability and optimality of multi-legged locomotion could be achieved using the proposed multi-scale neuro-cognitive model, from short to long-term adaptation, with efficient computational usage. Future research directions can be implemented not only in robotics contexts but also in the context of interdisciplinary studies incorporating cognitive science and ecological psychology.

Bilingualism is always cognitively advantageous, but this doesn't mean what you think it means

For decades now a research question has firmly established itself as a staple of psychological and neuroscientific investigations on language, namely the question of whether and how bilingualism is cognitively beneficial, detrimental or neutral. As more and more studies appear every year, it seems as though the research question itself is firmly grounded and can be answered if only we use the right experimental manipulations and subject the data to the right analysis methods and interpretive lens. In this paper we propose that, rather than merely improving prior methods in the pursuit of evidence in one direction or another, we would do well to carefully consider whether the research question itself is as firmly grounded as it might appear to be. We identify two bodies of research that suggest the research question to be highly problematic. In particular, drawing from work in sociolinguistics and in embodied cognitive science, we argue that the research question of whether bilingualism is cognitively advantageous or not is based on problematic assumptions about language and cognition. Once these assumptions are addressed head on, a straightforward answer to the question arises, but the question itself comes to seem to be a poor starting point for research. After examining why this is so, we conclude by exploring some implications for future research.

Combining Reflexes and External Sensory Information in a Neuromusculoskeletal Model to Control a Quadruped Robot

This article examines the importance of integrating locomotion and cognitive information for achieving dynamic locomotion from a viewpoint combining biology and ecological psychology. We present a mammalian neuromusculoskeletal model from external sensory information processing to muscle activation, which includes: 1) a visual-attention control mechanism for controlling attention to external inputs; 2) object recognition representing the primary motor cortex; 3) a motor control model that determines motor commands traveling down the corticospinal and reticulospinal tracts; 4) a central pattern generation model representing pattern generation in the spinal cord; and 5) a muscle reflex model representing the muscle model and its reflex mechanism. The proposed model is able to generate the locomotion of a quadruped robot in flat and natural terrain. The experiment also shows the importance of a postural reflex mechanism when experiencing a sudden obstacle. We show the reflex mechanism when a sudden obstacle is separately detected from both external (retina) and internal (touching afferent) sensory information. We present the biological rationale for supporting the proposed model. Finally, we discuss future contributions, trends, and the importance of the proposed research.

Natural behavior is the language of the brain

The breadth and complexity of natural behaviors inspires awe. Understanding how our perceptions, actions, and internal thoughts arise from evolved circuits in the brain has motivated neuroscientists for generations. Researchers have traditionally approached this question by focusing on stereotyped behaviors, either natural or trained, in a limited number of model species. This approach has allowed for the isolation and systematic study of specific brain operations, which has greatly advanced our understanding of the circuits involved. At the same time, the emphasis on experimental reductionism has left most aspects of the natural behaviors that have shaped the evolution of the brain largely unexplored. However, emerging technologies and analytical tools make it possible to comprehensively link natural behaviors to neural activity across a broad range of ethological contexts and timescales, heralding new modes of neuroscience focused on natural behaviors. Here we describe a three-part roadmap that aims to leverage the wealth of behaviors in their naturally occurring distributions, linking their variance with that of underlying neural processes to understand how the brain is able to successfully navigate the everyday challenges of animals' social and ecological landscapes. To achieve this aim, experimenters must harness one challenge faced by all neurobiological systems, namely variability, in order to gain new insights into the language of the brain.

Egocentric Chunking in the Predictive Brain: A Cognitive Basis of Expert Performance in High-Speed Sports

What principles and mechanisms allow humans to encode complex 3D information, and how can it be so fast, so accurately and so flexibly transformed into coordinated action? How do these processes work when developed to the limit of human physiological and cognitive capacity-as they are in high-speed sports, such as alpine skiing or motor racing? High-speed sports present not only physical challenges, but present some of the biggest perceptual-cognitive demands for the brain. The skill of these elite athletes is in many ways an attractive model for studying human performance "in the wild", and its neurocognitive basis. This article presents a framework theory for how these abilities may be realized in high-speed sports. It draws on a careful analysis of the case of the motorsport athlete, as well as theoretical concepts from: (1) cognitive neuroscience of wayfinding, steering, and driving; (2) cognitive psychology of expertise; (3) cognitive modeling and machine learning; (4) human-in-the loop modellling in vehicle system dynamics and human performance engineering; (5) experimental research (in the laboratory and in the field) on human visual guidance. The distinctive contribution is the way these are integrated, and the concept of chunking is used in a novel way to analyze a high-speed sport. The mechanisms invoked are domain-general, and not specific to motorsport or the use of a particular type of vehicle (or any vehicle for that matter); the egocentric chunking hypothesis should therefore apply to any dynamic task that requires similar core skills. It offers a framework for neuroscientists, psychologists, engineers, and computer scientists working in the field of expert sports performance, and may be useful in translating fundamental research into theory-based insight and recommendations for improving real-world elite performance. Specific experimental predictions and applicability of the hypotheses to other sports are discussed.

Avoiding obstacles while intercepting a moving target: a miniature fly's solution

The miniature robber fly Holcocephala fusca intercepts its targets with behaviour that is approximated by the proportional navigation guidance law. During predatory trials, we challenged the interception of H. fusca performance by placing a large object in its potential flight path. In response, H. fusca deviated from the path predicted by pure proportional navigation, but in many cases still eventually contacted the target. We show that such flight deviations can be explained as the output of two competing navigational systems: pure-proportional navigation and a simple obstacle avoidance algorithm. Obstacle avoidance by H. fusca is here described by a simple feedback loop that uses the visual expansion of the approaching obstacle to mediate the magnitude of the turning-away response. We name the integration of this steering law with proportional navigation 'combined guidance'. The results demonstrate that predatory intent does not operate a monopoly on the fly's steering when attacking a target, and that simple guidance combinations can explain obstacle avoidance during interceptive tasks.

Movement generalization of variable initial task state based on Euclidean transformation dynamical movement primitives

Robots need the ability to tackle problems of movement generalization in variable task state and complex environment. Dynamical movement primitives can effectively endow robots with humanoid characteristics. However, when the initial state of tasks changes, the generalized trajectories by dynamical movement primitives cannot retain shape features of demonstration, resulting in the loss of imitation quality. In this article, a modified dynamical movement primitives based on Euclidean transformation is proposed to solve this problem. It transforms the initial task state to a virtual situation similar to the demonstration and then utilizes the dynamical movement primitive method to realize movement generalization. Finally, it reverses the movement back to the real situation. Besides, the information of obstacles is added to Euclidean transformation based dynamical movement primitives framework to endow robots with the ability of obstacle avoidance. The normalized root-mean-square error is proposed as the criterion to evaluate the imitation similarity. The feasibility of this method is verified through writing letters, wiping whiteboard in two-dimensional task, and stirring mixture in three-dimensional task. The results show that the similarity of movement imitation in the proposed method is higher than dynamical movement primitives when the initial state changes. Meanwhile, Euclidean transformation based dynamical movement primitives can still greatly retain shape feature of demonstration while avoiding obstacles in an unstructured environment.

The Markov blanket trick: On the scope of the free energy principle and active inference

The free energy principle (FEP) has been presented as a unified brain theory, as a general principle for the self-organization of biological systems, and most recently as a principle for a theory of every thing. Additionally, active inference has been proposed as the process theory entailed by FEP that is able to model the full range of biological and cognitive events. In this paper, we challenge these two claims. We argue that FEP is not the general principle it is claimed to be, and that active inference is not the all-encompassing process theory it is purported to be either. The core aspects of our argumentation are that (i) FEP is just a way to generalize Bayesian inference to all domains by the use of a Markov blanket formalism, a generalization we call the Markov blanket trick; and that (ii) active inference presupposes successful perception and action instead of explaining them.

Navigational Behavior of Humans and Deep Reinforcement Learning Agents

Rapid advances in the field of Deep Reinforcement Learning (DRL) over the past several years have led to artificial agents (AAs) capable of producing behavior that meets or exceeds human-level performance in a wide variety of tasks. However, research on DRL frequently lacks adequate discussion of the low-level dynamics of the behavior itself and instead focuses on meta-level or global-level performance metrics. In doing so, the current literature lacks perspective on the qualitative nature of AA behavior, leaving questions regarding the spatiotemporal patterning of their behavior largely unanswered. The current study explored the degree to which the navigation and route selection trajectories of DRL agents (i.e., AAs trained using DRL) through simple obstacle ridden virtual environments were equivalent (and/or different) from those produced by human agents. The second and related aim was to determine whether a task-dynamical model of human route navigation could not only be used to capture both human and DRL navigational behavior, but also to help identify whether any observed differences in the navigational trajectories of humans and DRL agents were a function of differences in the dynamical environmental couplings.

Between-site equivalence of turning speed assessments using inertial measurement units

BACKGROUND

Turning is a component of gait that requires planning for movement of multiple body segments and the sophisticated integration of sensory information from the vestibular, visual, and somatosensory systems. These aspects of turning have led to growing interest to quantify turning in clinical populations to characterize deficits or identify disease progression. However, turning may be affected by environmental differences, and the degree to which turning assessments are comparable across research or clinical sites has not yet been evaluated.

RESEARCH QUESTION

The aim of this study was to determine the extent to which peak turning speeds are equivalent between two sites for a variety of mobility tasks.

METHODS

Data were collected at two different sites using separate healthy young adult participants (n = 47 participants total), but recruited using identical inclusion and exclusion criteria. Participants at each site completed three turning tasks: a one-minute walk (1 MW) along a six-meter walkway, a modified Illinois Agility Test (mIAT), and a custom clinical turning course (CCTC). Peak yaw turning speeds were extracted from wearable inertial sensors on the head, trunk, and pelvis. Between-site differences and two one-sided tests (TOST) were used to determine equivalence between sites, based on a minimum effect size reported between individuals with mild traumatic brain injury and healthy control subjects.

RESULTS

No outcomes were different between sites, and equivalence was determined for 6/21 of the outcomes. These findings suggest that some turning tasks and outcome measures may be better suited for multi-site studies. The equivalence results are also dependent on the minimum effect size of interest; nearly all outcomes were equivalent across sites when larger minimum effect sizes of interest were used.

SIGNIFICANCE

Together, these results suggest some tasks and outcome measures may be better suited for multi-site studies and literature-based comparisons.

Parietal maps of visual signals for bodily action planning

The posterior parietal cortex (PPC) has long been understood as a high-level integrative station for computing motor commands for the body based on sensory (i.e., mostly tactile and visual) input from the outside world. In the last decade, accumulating evidence has shown that the parietal areas not only extract the pragmatic features of manipulable objects, but also subserve sensorimotor processing of others’ actions. A paradigmatic case is that of the anterior intraparietal area (AIP), which encodes the identity of observed manipulative actions that afford potential motor actions the observer could perform in response to them. On these bases, we propose an AIP manipulative action-based template of the general planning functions of the PPC and review existing evidence supporting the extension of this model to other PPC regions and to a wider set of actions: defensive and locomotor actions. In our model, a hallmark of PPC functioning is the processing of information about the physical and social world to encode potential bodily actions appropriate for the current context. We further extend the model to actions performed with man-made objects (e.g., tools) and artifacts, because they become integral parts of the subject’s body schema and motor repertoire. Finally, we conclude that existing evidence supports a generally conserved neural circuitry that transforms integrated sensory signals into the variety of bodily actions that primates are capable of preparing and performing to interact with their physical and social world.

Icy road ahead-rapid adjustments of gaze-gait interactions during perturbed naturalistic walking

Most humans can walk effortlessly across uniform terrain even when they do not pay much attention to it. However, most natural terrain is far from uniform, and we need visual information to maintain stable gait. Recent advances in mobile eye-tracking technology have made it possible to study, in natural environments, how terrain affects gaze and thus the sampling of visual information. However, natural environments provide only limited experimental control, and some conditions cannot safely be tested. Typical laboratory setups, in contrast, are far from natural settings for walking. We used a setup consisting of a dual-belt treadmill, 240∘ projection screen, floor projection, three-dimensional optical motion tracking, and mobile eye tracking to investigate eye, head, and body movements during perturbed and unperturbed walking in a controlled yet naturalistic environment. In two experiments (N = 22 each), we simulated terrain difficulty by repeatedly inducing slipping through accelerating either of the two belts rapidly and unpredictably (Experiment 1) or sometimes following visual cues (Experiment 2). We quantified the distinct roles of eye and head movements for adjusting gaze on different time scales. While motor perturbations mainly influenced head movements, eye movements were primarily affected by the presence of visual cues. This was true both immediately following slips and—to a lesser extent—over the course of entire 5-min blocks. We find adapted gaze parameters already after the first perturbation in each block, with little transfer between blocks. In conclusion, gaze–gait interactions in experimentally perturbed yet naturalistic walking are adaptive, flexible, and effector specific.

Target position and avoidance margin effects on path planning in obstacle avoidance

This study examined how people choose their path to a target, and the visual information they use for path planning. Participants avoided stepping outside an avoidance margin between a stationary obstacle and the edge of a walkway as they walked to a bookcase and picked up a target from different locations on a shelf. We provided an integrated explanation for path selection by combining avoidance margin, deviation angle, and distance to the obstacle. We found that the combination of right and left avoidance margins accounted for 26%, deviation angle accounted for 39%, and distance to the obstacle accounted for 35% of the variability in decisions about the direction taken to circumvent an obstacle on the way to a target. Gaze analysis findings showed that participants directed their gaze to minimize the uncertainty involved in successful task performance and that gaze sequence changed with obstacle location. In some cases, participants chose to circumvent the obstacle on a side for which the gaze time was shorter, and the path was longer than for the opposite side. Our results of a path selection judgment test showed that the threshold for participants abandoning their preferred side for circumventing the obstacle was a target location of 15 cm to the left of the bookcase shelf center.

A Dynamical Generative Model of Social Interactions

The ability to make accurate social inferences makes humans able to navigate and act in their social environment effortlessly. Converging evidence shows that motion is one of the most informative cues in shaping the perception of social interactions. However, the scarcity of parameterized generative models for the generation of highly-controlled stimuli has slowed down both the identification of the most critical motion features and the understanding of the computational mechanisms underlying their extraction and processing from rich visual inputs. In this work, we introduce a novel generative model for the automatic generation of an arbitrarily large number of videos of socially interacting agents for comprehensive studies of social perception. The proposed framework, validated with three psychophysical experiments, allows generating as many as 15 distinct interaction classes. The model builds on classical dynamical system models of biological navigation and is able to generate visual stimuli that are parametrically controlled and representative of a heterogeneous set of social interaction classes. The proposed method represents thus an important tool for experiments aimed at unveiling the computational mechanisms mediating the perception of social interactions. The ability to generate highly-controlled stimuli makes the model valuable not only to conduct behavioral and neuroimaging studies, but also to develop and validate neural models of social inference, and machine vision systems for the automatic recognition of social interactions. In fact, contrasting human and model responses to a heterogeneous set of highly-controlled stimuli can help to identify critical computational steps in the processing of social interaction stimuli.

The impact of smartphone use on gait in young adults: Cognitive load vs posture of texting

Many researches have reported that the use of smartphones has a negative impact on gait variability and speed of pedestrians by dispersion of cognition, but the influence of factors other than cognitive function on gait is still unclear. The purpose of this study was to investigate the impact of smartphone use on spatiotemporal gait parameters in healthy young people while walking. 42 healthy young adults were recruited and instructed to walk in four conditions (walking without using a smartphone, typing on a smartphone with both hands, typing on a smartphone with one hand, and texting posture with non-task). All spatiotemporal gait parameters were measured using the GAITRite walkway. Compared to walking without using a smartphone, the subjects walked with a slower cadence and velocity and changed stride length and gait cycle and spent more time in contact with the ground when using a smartphone (p < 0.05). In addition, even if a texting posture was taken without performing a task, a similar change was observed when using a smartphone (p < 0.05). This study found that a cautious gait pattern occurred due to smartphone use, and that a change in gait appeared just by taking a posture without using smartphone.

Limb movements of another pedestrian affect crossing distance but not path planning during virtual over ground circumvention

Circumventing another pedestrian is a frequent daily activity. The literature has provided a better understanding about anticipatory locomotor adjustments based on global (whole body) movement, but how local limb movements of another pedestrian affect one's circumvention is not well known. The purpose of this study was to understand how local limb movements of another pedestrian affect the planning and execution to circumvent them. Ten healthy young adults (24.5 ± 3.0 years) were immersed in a virtual environment representing a shopping mall. Participants walked to a shop located directly in front of them while circumventing a virtual agent which, when present, approached from straight ahead with one of four different locomotor patterns: 1-Normal locomotor movements; 2- No arm movements; 3- No leg movements; 4- No arm and leg movements (gliding to them). Circumvention trajectory, minimum clearance and coordination of head and trunk rotations along with center of mass lateral displacement were examined. Nonparametric Analysis of Longitudinal Data was used to compare variables across the different conditions. Minimum clearance was smaller for normal locomotor movements compared to all other conditions, but coordination of body movements and onset of circumvention trajectory deviations remained unchanged. These results suggest that global body movement is sufficient to plan circumvention trajectories in a predictable avoidance task, but clearance safety margins are influenced by the local limb movements of another pedestrian.

Route selection in barrier avoidance

BACKGROUND

Fajen and Warren's steering dynamics model can reproduce human paths around an extended barrier by adding 'waypoints' at each end - if one waypoint is selected to minimize the global path curvature (Gérin-Lajoie and Warren, 2008). We propose that waypoint selection behaves like a choice between two competing goals, in which the smaller distance (d) and deviation angle (β) is preferred (Ulrich and Borenstein, 1998). Here we manipulate these two variables to test the determinants of route selection.

RESEARCH QUESTION

How does route selection in barrier avoidance depend on the local distance (d) and deviation angle (β) of each end, and on global path length (P) and curvature (C)?

METHODS

Participants (Exp1 N = 19; Exp2 N = 15) walked around a barrier to a visible goal in a virtual environment. Barrier orientation and lateral position were manipulated to vary the difference in distance (Δd) and in deviation angle (Δβ) between the left and right ends of the barrier. Left/Right route data were analyzed using a mixed-effects logistic regression model, with Δβ, Δd, and observed ΔP and ΔC as predictors.

RESULTS

The main effects of Δβ and Δd significantly predicted Rightward responses (p < .001), more strongly than ΔP and ΔC (ΔBIC = 29.5). When Δβ and Δd agreed, responses were toward the smaller distance and deviation (88% overall); when they conflicted, responses were in between (65% toward smaller β). The 75% choice threshold for Δβ was ±1.65˚, and for Δd was 0.75 m, from the 50% chance level.

SIGNIFICANCE

During barrier avoidance, participants select a route that minimizes the local distance (d) and deviation angle (β) of the waypoint, rather than the global path length (P) or path curvature (C). These findings support the hypothesis that route selection is governed by competing waypoints, instead of comparing planned paths to the final goal.

Defining cricket batting expertise from the perspective of elite coaches

Traditionally in sporting tasks, expertise has been thought of as the attainment of near flawless technical abilities. While contemporary views have become more holistic in nature, in certain sporting domains it is still not clear what exactly encapsulates expertise. This study sought to further understand the crucial and defining characteristics of cricket batting; a complex and difficult perceptual-motor skill with minimal error tolerance and severe time constraints. Eight elite cricket batting coaches, who themselves were former international or state level batsmen, were interviewed to identify characteristics of cricket batting expertise. From this, a conceptual model was developed in relation to an expert within their performance environment. This model highlights several key factors experts possess beyond just technical proficiency, such as self-awareness of their technical and tactical strengths in relation to the situation of the game; self-regulatory behaviours to problem solve performance challenges in-game; and psychological strategies such as between-ball routines to manage cognitions and emotions. The conceptual model of batting expertise described in this paper is designed to introduce an order to how these various skills, possessed by an expert batter, interact within the performance environment to interpret expert performance.

Learning to Avoid Obstacles With Minimal Intervention Control

Programming by demonstration has received much attention as it offers a general framework which allows robots to efficiently acquire novel motor skills from a human teacher. While traditional imitation learning that only focuses on either Cartesian or joint space might become inappropriate in situations where both spaces are equally important (e.g., writing or striking task), hybrid imitation learning of skills in both Cartesian and joint spaces simultaneously has been studied recently. However, an important issue which often arises in dynamical or unstructured environments is overlooked, namely how can a robot avoid obstacles? In this paper, we aim to address the problem of avoiding obstacles in the context of hybrid imitation learning. Specifically, we propose to tackle three subproblems: (i) designing a proper potential field so as to bypass obstacles, (ii) guaranteeing joint limits are respected when adjusting trajectories in the process of avoiding obstacles, and (iii) determining proper control commands for robots such that potential human-robot interaction is safe. By solving the aforementioned subproblems, the robot is capable of generalizing observed skills to new situations featuring obstacles in a feasible and safe manner. The effectiveness of the proposed method is validated through a toy example as well as a real transportation experiment on the iCub humanoid robot.

Gaze-behaviors of runners in a natural, urban running environment

Gaze-tracking techniques have advanced our understanding of visual attention and decision making during walking and athletic events, but little is known about how vision influences behavior during running over common, natural obstacles. This study tested hypotheses about whether runners regularly collect visual information and pre-plan obstacle clearance (feedforward control), make improvisational adjustments (online control), or some combination of both. In this study, the gaze profiles of 5 male and 5 female runners, fitted with a telemetric gaze-tracking device, were used to identify the frequency of fixations on an obstacle during a run. Overall, participants fixated on the obstacle 2.4 times during the run, with the last fixation occurring on average between 40% and 80% of the run, suggesting runners potentially shifted from a feedforward planning strategy to an online control strategy during the late portions of the running trial. A negative association was observed between runner velocity and average number of fixations. Consistent with previous studies on visual strategies used during walking, our results indicate that visual attentiveness is part of an important feedforward strategy for runners allowing them to safely approach an obstacle. Thus, visual obstacle attention is a key factor in the navigation of complex, natural landscapes while running.

Collision avoidance behaviours when circumventing people of different sizes in various positions and locations

The current study examined whether young adults' avoidance behaviours differed when circumventing a larger versus smaller interferer. It was expected that avoidance behaviours (repulsion) would be affected by the interferer's size (i.e., greater repulsion for larger body size). Participants (n = 20) walked along an 8 m pathway towards a goal while avoiding either a larger or smaller sized male interferer who stood stationary facing forward, backward, left, or right and were located 2, 4, or 6 m from the participants' starting position. Results revealed that there was an effect of interferer body size (personal-characteristics) and orientation (situational-characteristics) on M-L clearance between the interferer and participant at the time of crossing, suggesting that repulsion magnitudes are scaled to an interferer's closest body surface.

How perception of personal space influence obstacle avoidance during walking: differences between young and older adults

OBJECTIVE

Individuals maintain a spatial margin or 'personal space' between themselves and others. The form of this space and strategies for avoiding obstacles can be influenced by participant characteristics such as age. In this study, we investigated the characteristics of personal space and obstacle avoidance strategies in young and older adults. We also examined differences in perceptual personal space and walking trajectory during obstacle avoidance using a three-dimensional motion capture system. Methods Ten young adults and ten older adults participated in this study. We calculated actual obstacle avoidance trajectory and obstacle avoidance data such as the lateral spatial margin and body rotation angle during walking in a task that included obstacle avoidance. We also measured the perceptual personal space created by approaching a confederate. In order to calculate each personal space and obstacle avoidance data, we used a three-dimensional motion capture system. Two factors (two groups and personal space) of repeated analysis of variance were used in statistical analysis. Results We found no age-related differences in personal space or obstacle avoidance strategy in this study (F = 0.52, p = 0.48). However, we found significant differences in the form of perceptual personal space and personal space formed during obstacle avoidance (F = 11.86, p = 0.0030). Conclusion This study indicates that perceptual personal space did not reflect the walking trajectory created by actual obstacle avoidance. In addition, age did not influence the obstacle avoidance strategy. These results suggest that the perceptual personal space and aging have little effect in the situation of avoiding a single standing pedestrian.

How biomechanics, path planning and sensing enable gliding flight in a natural environment

Gliding animals traverse cluttered aerial environments when performing ecologically relevant behaviours. However, it is unknown how gliders execute collision-free flight over varying distances to reach their intended target. We quantified complete glide trajectories amid obstacles in a naturally behaving population of gliding lizards inhabiting a rainforest reserve. In this cluttered habitat, the lizards used glide paths with fewer obstacles than alternatives of similar distance. Their takeoff direction oriented them away from obstacles in their path and they subsequently made mid-air turns with accelerations of up to 0.5 g to reorient towards the target tree. These manoeuvres agreed well with a vision-based steering model which maximized their bearing angle with the obstacle while minimizing it with the target tree. Nonetheless, negotiating obstacles reduced mid-glide shallowing rates, implying greater loss of altitude. Finally, the lizards initiated a pitch-up landing manoeuvre consistent with a visual trigger model, suggesting that the landing decision was based on the optical size and speed of the target. They subsequently followed a controlled-collision approach towards the target, ending with variable impact speeds. Overall, the visually guided path planning strategy that enabled collision-free gliding required continuous changes in the gliding kinematics such that the lizards never attained theoretically ideal steady-state glide dynamics.

Developmental Designs and Adult Functions of Cortical Maps in Multiple Modalities: Perception, Attention, Navigation, Numbers, Streaming, Speech, and Cognition

This article unifies neural modeling results that illustrate several basic design principles and mechanisms that are used by advanced brains to develop cortical maps with multiple psychological functions. One principle concerns how brains use a strip map that simultaneously enables one feature to be represented throughout its extent, as well as an ordered array of another feature at different positions of the strip. Strip maps include circuits to represent ocular dominance and orientation columns, place-value numbers, auditory streams, speaker-normalized speech, and cognitive working memories that can code repeated items. A second principle concerns how feature detectors for multiple functions develop in topographic maps, including maps for optic flow navigation, reinforcement learning, motion perception, and category learning at multiple organizational levels. A third principle concerns how brains exploit a spatial gradient of cells that respond at an ordered sequence of different rates. Such a rate gradient is found along the dorsoventral axis of the entorhinal cortex, whose lateral branch controls the development of time cells, and whose medial branch controls the development of grid cells. Populations of time cells can be used to learn how to adaptively time behaviors for which a time interval of hundreds of milliseconds, or several seconds, must be bridged, as occurs during trace conditioning. Populations of grid cells can be used to learn hippocampal place cells that represent the large spaces in which animals navigate. A fourth principle concerns how and why all neocortical circuits are organized into layers, and how functionally distinct columns develop in these circuits to enable map development. A final principle concerns the role of Adaptive Resonance Theory top-down matching and attentional circuits in the dynamic stabilization of early development and adult learning. Cortical maps are modeled in visual, auditory, temporal, parietal, prefrontal, entorhinal, and hippocampal cortices.

Behavioral Dynamics of Pedestrians Crossing between Two Moving Vehicles

This study examines the human behavioral dynamics of pedestrians crossing a street with vehicular traffic. To this end, an experiment was constructed in which human participants cross a road between two moving vehicles in a virtual reality setting. A mathematical model is developed in which the position is given by a simple function. The model is used to extract information on each crossing by performing root-mean-square deviation (RMSD) minimization of the function from the data. By isolating the parameter adjusted to gap features, we find that the subjects primarily changed the timing of the acceleration to adjust to changing gap conditions, rather than walking speed or duration of acceleration. Moreover, this parameter was also adjusted to the vehicle speed and vehicle type, even when the gap size and timing were not changed. The model is found to provide a description of gap affordance via a simple inequality of the fitting parameters. In addition, the model turns out to predict a constant bearing angle with the crossing point, which is also observed in the data. We thus conclude that our model provides a mathematical tool useful for modeling crossing behaviors and probing existing models. It may also provide insight into the source of traffic accidents.

Neural Networks Mediating Perceptual Learning in Congenital Blindness

Despite the fact that complete visual deprivation leads to volumetric reductions in brain structures associated with spatial learning, blind individuals are still able to navigate. The neural structures involved in this function are not fully understood. Our study aims to correlate the performance of congenitally blind individuals (CB) and blindfolded sighted controls (SC) in a life-size obstacle-course using a visual-to-tactile sensory substitution device, with the size of brain structures (voxel based morphometry-VBM-) measured through structural magnetic resonance Imaging (MRI). VBM was used to extract grey matter volumes within several a-priori defined brain regions in all participants. Principal component analysis was utilized to group brain regions in factors and orthogonalize brain volumes. Regression analyses were then performed to link learning abilities to these factors. We found that (1) both CB and SC were able to learn to detect and avoid obstacles; (2) their learning rates for obstacle detection and avoidance correlated significantly with the volume of brain structures known to be involved in spatial skills. There is a similar relation between regions of the dorsal stream network and avoidance for both SC and CB whereas for detection, SC rely more on medial temporal lobe structures and CB on sensorimotor areas.

How Does a Walker Pass Between Two People Standing in Different Configurations? Influence of Personal Space on Aperture Passing Methods

Most studies on aperture passability focus on aperture passing involving non-human physical objects. In this study, we examined experimentally how participants pass between two box-shaped frames and between the same frames, each with a human confederate in it, facing various directions. Seven configuration conditions were set up, six of which differed in terms of the human confederates’ sets of directions in the two frames: face-to-face, back-to-back, facing toward or away from the participants, facing leftward or rightward from the participants’ perspective, and the empty frames condition without human confederates. There were seven aperture-width conditions—50, 55, 60, 65, 70, 75, and 80 cm—and participants walked at their normal speed through the apertures. We found that the participants’ shoulder rotation angle in the face-to-face condition was significantly greater than that in the empty frames condition. Further, the participants preferred to rotate their shoulders counterclockwise when our confederates in the aperture faced leftward, and clockwise, when they faced rightward. These results suggest that people change their passing-through methods by considering the social nature of the aperture as well as its width.

Getting Back Into the Loop: The Perceptual-Motor Determinants of Successful Transitions out of Automated Driving

OBJECTIVE

To present a structured, narrative review highlighting research into human perceptual-motor coordination that can be applied to automated vehicle (AV)-human transitions.

BACKGROUND

Manual control of vehicles is made possible by the coordination of perceptual-motor behaviors (gaze and steering actions), where active feedback loops enable drivers to respond rapidly to ever-changing environments. AVs will change the nature of driving to periods of monitoring followed by the human driver taking over manual control. The impact of this change is currently poorly understood.

METHOD

We outline an explanatory framework for understanding control transitions based on models of human steering control. This framework can be summarized as a perceptual-motor loop that requires (a) calibration and (b) gaze and steering coordination. A review of the current experimental literature on transitions is presented in the light of this framework.

RESULTS

The success of transitions are often measured using reaction times, however, the perceptual-motor mechanisms underpinning steering quality remain relatively unexplored.

CONCLUSION

Modeling the coordination of gaze and steering and the calibration of perceptual-motor control will be crucial to ensure safe and successful transitions out of automated driving.

APPLICATION

This conclusion poses a challenge for future research on AV-human transitions. Future studies need to provide an understanding of human behavior that will be sufficient to capture the essential characteristics of drivers reengaging control of their vehicle. The proposed framework can provide a guide for investigating specific components of human control of steering and potential routes to improving manual control recovery.

Ecological mechanisms in cognitive science

In 2010, Bechtel and Abrahamsen defined and described what it means to be a dynamic causal mechanistic explanatory model. They discussed the development of a mechanistic explanation of circadian rhythms as an exemplar of the process and challenged cognitive science to follow this example. This article takes on that challenge. A mechanistic model is one that accurately represents the real parts and operations of the mechanism being studied. These real components must be identified by an empirical programme that decomposes the system at the correct scale and localises the components in space and time. Psychological behaviour emerges from the nature of our real-time interaction with our environments—here we show that the correct scale to guide decomposition is picked out by the ecological perceptual information that enables that interaction. As proof of concept, we show that a simple model of coordinated rhythmic movement, grounded in information, is a genuine dynamical mechanistic explanation of many key coordination phenomena.

The flexible action system: Click-based echolocation may replace certain visual functionality for adaptive walking

People use sensory, in particular visual, information to guide actions such as walking around obstacles, grasping or reaching. However, it is presently unclear how malleable the sensorimotor system is. The present study investigated this by measuring how click-based echolocation may be used to avoid obstacles while walking. We tested 7 blind echolocation experts, 14 sighted, and 10 blind echolocation beginners. For comparison, we also tested 10 sighted participants, who used vision. To maximize the relevance of our research for people with vision impairments, we also included a condition where the long cane was used and considered obstacles at different elevations. Motion capture and sound data were acquired simultaneously. We found that echolocation experts walked just as fast as sighted participants using vision, and faster than either sighted or blind echolocation beginners. Walking paths of echolocation experts indicated early and smooth adjustments, similar to those shown by sighted people using vision and different from later and more abrupt adjustments of beginners. Further, for all participants, the use of echolocation significantly decreased collision frequency with obstacles at head, but not ground level. Further analyses showed that participants who made clicks with higher spectral frequency content walked faster, and that for experts higher clicking rates were associated with faster walking. The results highlight that people can use novel sensory information (here, echolocation) to guide actions, demonstrating the action system’s ability to adapt to changes in sensory input. They also highlight that regular use of echolocation enhances sensory-motor coordination for walking in blind people.

Vision loss has negative consequences for people’s mobility. The current report demonstrates that echolocation might replace certain visual functionality for adaptive walking. Importantly, the report also highlights that echolocation and long cane are complementary mobility techniques. The findings have direct relevance for professionals involved in mobility instruction and for people who are blind.

Local interactions underlying collective motion in human crowds

It is commonly believed that global patterns of motion in flocks, schools and crowds emerge from local interactions between individuals, through a process of self-organization. The key to explaining such collective behaviour thus lies in deciphering these local interactions. We take an experiment-driven approach to modelling collective motion in human crowds. Previously, we observed that a pedestrian aligns their velocity vector (speed and heading direction) with that of a neighbour. Here we investigate the neighbourhood of interaction in a crowd: which neighbours influence a pedestrian's behaviour, how this depends on neighbour position, and how the influences of multiple neighbours are combined. In three experiments, a participant walked in a virtual crowd whose speed and heading were manipulated. We find that neighbour influence is linearly combined and decreases with distance, but not with lateral position (eccentricity). We model the neighbourhood as (i) a circularly symmetric region with (ii) a weighted average of neighbours, (iii) a uni-directional influence, and (iv) weights that decay exponentially to zero by 5 m. The model reproduces the experimental data and predicts individual trajectories in observational data on a human 'swarm'. The results yield the first bottom-up model of collective crowd motion.