7,146 research outputs found
How self-regulation, the storage effect and their interaction contribute to coexistence in stochastic and seasonal environments
Explaining coexistence in species-rich communities of primary producers
remains a challenge for ecologists because of their likely competition for
shared resources. Following Hutchinson's seminal suggestion, many theoreticians
have tried to create diversity through a fluctuating environment, which impairs
or slows down competitive exclusion. However, fluctuating-environment models
often only produce a dozen of coexisting species at best. Here, we investigate
how to create richer communities in fluctuating environments, using an
empirically parameterized model. Building on the forced Lotka-Volterra model of
Scranton and Vasseur (Theor Ecol 9(3):353-363, 2016), inspired by phytoplankton
communities, we have investigated the effect of two coexistence mechanisms,
namely the storage effect and higher intra- than interspecific competition
strengths (i.e., strong self-regulation). We tuned the intra/inter competition
ratio based on empirical analyses, in which self-regulation dominates
interspecific interactions. Although a strong self-regulation maintained more
species (50%) than the storage effect (25%), we show that none of the two
coexistence mechanisms considered could ensure the coexistence of all species
alone. Realistic seasonal environments only aggravated that picture, as they
decreased persistence relative to a random environment. However, strong
self-regulation and the storage effect combined superadditively so that all
species could persist with both mechanisms at work. Our results suggest that
combining different coexistence mechanisms into community models might be more
fruitful than trying to find which mechanism best explains diversity. We
additionally highlight that while biomass-trait distributions provide some
clues regarding coexistence mechanisms, they cannot indicate unequivocally
which mechanisms are at play.Comment: 27 pages, 9 figures, Theor Ecol (2019
Timing and correction of stepping movements with a virtual reality avatar
Research into the ability to coordinate one’s movements with external cues has focussed on the use of simple rhythmic, auditory and visual stimuli, or interpersonal coordination with another person. Coordinating movements with a virtual avatar has not been explored, in the context of responses to temporal cues. To determine whether cueing of movements using a virtual avatar is effective, people’s ability to accurately coordinate with the stimuli needs to be investigated. Here we focus on temporal cues, as we know from timing studies that visual cues can be difficult to follow in the timing context.
Real stepping movements were mapped onto an avatar using motion capture data. Healthy participants were then motion captured whilst stepping in time with the avatar’s movements, as viewed through a virtual reality headset. The timing of one of the avatar step cycles was accelerated or decelerated by 15% to create a temporal perturbation, for which participants would need to correct to, in order to remain in time. Step onset times of participants relative to the corresponding step-onsets of the avatar were used to measure the timing errors (asynchronies) between them. Participants completed either a visual-only condition, or auditory-visual with footstep sounds included, at two stepping tempo conditions (Fast: 400ms interval, Slow: 800ms interval).
Participants’ asynchronies exhibited slow drift in the Visual-Only condition, but became stable in the Auditory-Visual condition. Moreover, we observed a clear corrective response to the phase perturbation in both the fast and slow tempo auditory-visual conditions.
We conclude that an avatar’s movements can be used to influence a person’s own motion, but should include relevant auditory cues congruent with the movement to ensure a suitable level of entrainment is achieved. This approach has applications in physiotherapy, where virtual avatars present an opportunity to provide the guidance to assist patients in adhering to prescribed exercises
Social Conformity Despite Individual Preferences for Distinctiveness
We demonstrate that individual behaviors directed at the attainment of
distinctiveness can in fact produce complete social conformity. We thus offer
an unexpected generative mechanism for this central social phenomenon.
Specifically, we establish that agents who have fixed needs to be distinct and
adapt their positions to achieve distinctiveness goals, can nevertheless
self-organize to a limiting state of absolute conformity. This seemingly
paradoxical result is deduced formally from a small number of natural
assumptions, and is then explored at length computationally. Interesting
departures from this conformity equilibrium are also possible, including
divergence in positions. The effect of extremist minorities on these dynamics
is discussed. A simple extension is then introduced, which allows the model to
generate and maintain social diversity, including multimodal distinctiveness
distributions. The paper contributes formal definitions, analytical deductions,
and counterintuitive findings to the literature on individual distinctiveness
and social conformity.Comment: 11 pages, 6 figures, appendi
The multisensory body revealed through its cast shadows
One key issue when conceiving the body as a multisensory object is how the cognitive
system integrates visible instances of the self and other bodies with one\u2019s own
somatosensory processing, to achieve self-recognition and body ownership. Recent
research has strongly suggested that shadows cast by our own body have a special
status for cognitive processing, directing attention to the body in a fast and highly specific
manner. The aim of the present article is to review the most recent scientific contributions
addressing how body shadows affect both sensory/perceptual and attentional processes.
The review examines three main points: (1) body shadows as a special window to
investigate the construction of multisensory body perception; (2) experimental paradigms
and related findings; (3) open questions and future trajectories. The reviewed literature
suggests that shadows cast by one\u2019s own body promote binding between personal
and extrapersonal space and elicit automatic orienting of attention toward the bodypart
casting the shadow. Future research should address whether the effects exerted
by body shadows are similar to those observed when observers are exposed to other
visual instances of their body. The results will further clarify the processes underlying the
merging of vision and somatosensation when creating body representations
Investigation of the Sense of Agency in Social Cognition, based on frameworks of Predictive Coding and Active Inference: A simulation study on multimodal imitative interaction
When agents interact socially with different intentions, conflicts are
difficult to avoid. Although how agents can resolve such problems autonomously
has not been determined, dynamic characteristics of agency may shed light on
underlying mechanisms. The current study focused on the sense of agency (SoA),
a specific aspect of agency referring to congruence between the agent's
intention in acting and the outcome. Employing predictive coding and active
inference as theoretical frameworks of perception and action generation, we
hypothesize that regulation of complexity in the evidence lower bound of an
agent's model should affect the strength of the agent's SoA and should have a
critical impact on social interactions. We built a computational model of
imitative interaction between a robot and a human via visuo-proprioceptive
sensation with a variational Bayes recurrent neural network, and simulated the
model in the form of pseudo-imitative interaction using recorded human body
movement data. A key feature of the model is that each modality's complexity
can be regulated differently with a hyperparameter assigned to each module. We
first searched for an optimal setting that endows the model with appropriate
coordination of multimodal sensation. This revealed that the vision module's
complexity should be more tightly regulated than that of the proprioception
module. Using the optimally trained model, we examined how changing the
tightness of complexity regulation after training affects the strength of the
SoA during interactions. The results showed that with looser regulation, an
agent tends to act more egocentrically, without adapting to the other. In
contrast, with tighter regulation, the agent tends to follow the other by
adjusting its intention. We conclude that the tightness of complexity
regulation crucially affects the strength of the SoA and the dynamics of
interactions between agents.Comment: 23 pages, 8 figure
Real Time Animation of Virtual Humans: A Trade-off Between Naturalness and Control
Virtual humans are employed in many interactive applications using 3D virtual environments, including (serious) games. The motion of such virtual humans should look realistic (or ‘natural’) and allow interaction with the surroundings and other (virtual) humans. Current animation techniques differ in the trade-off they offer between motion naturalness and the control that can be exerted over the motion. We show mechanisms to parametrize, combine (on different body parts) and concatenate motions generated by different animation techniques. We discuss several aspects of motion naturalness and show how it can be evaluated. We conclude by showing the promise of combinations of different animation paradigms to enhance both naturalness and control
Cooperative Particle Swarm Optimization for Combinatorial Problems
A particularly successful line of research for numerical optimization is the well-known computational paradigm particle swarm optimization (PSO). In the PSO framework, candidate solutions are represented as particles that have a position and a velocity in a multidimensional search space. The direct representation of a candidate solution as a point that flies through hyperspace (i.e., Rn) seems to strongly predispose the PSO toward continuous optimization. However, while some attempts have been made towards developing PSO algorithms for combinatorial problems, these techniques usually encode candidate solutions as permutations instead of points in search space and rely on additional local search algorithms.
In this dissertation, I present extensions to PSO that by, incorporating a cooperative strategy, allow the PSO to solve combinatorial problems. The central hypothesis is that by allowing a set of particles, rather than one single particle, to represent a candidate solution, combinatorial problems can be solved by collectively constructing solutions. The cooperative strategy partitions the problem into components where each component is optimized by an individual particle. Particles move in continuous space and communicate through a feedback mechanism. This feedback mechanism guides them in the assessment of their individual contribution to the overall solution.
Three new PSO-based algorithms are proposed. Shared-space CCPSO and multispace CCPSO provide two new cooperative strategies to split the combinatorial problem, and both models are tested on proven NP-hard problems. Multimodal CCPSO extends these combinatorial PSO algorithms to efficiently sample the search space in problems with multiple global optima. Shared-space CCPSO was evaluated on an abductive problem-solving task: the construction of parsimonious set of independent hypothesis in diagnostic problems with direct causal links between disorders and manifestations. Multi-space CCPSO was used to solve a protein structure prediction subproblem, sidechain packing. Both models are evaluated against the provable optimal solutions and results show that both proposed PSO algorithms are able to find optimal or near-optimal solutions. The exploratory ability of multimodal CCPSO is assessed by evaluating both the quality and diversity of the solutions obtained in a protein sequence design problem, a highly multimodal problem. These results provide evidence that extended PSO algorithms are capable of dealing with combinatorial problems without having to hybridize the PSO with other local search techniques or sacrifice the concept of particles moving throughout a continuous search space
- …