Feeling of hand deformation as a monkey's hand: an experiment on a visual body with discomfort and its algebraic analysis.

While there are many studies in which body ownership can be transferred to a virtual body, there are few experimental studies of how subjects feel about their own bodies being deformed since a real body cannot be deformed. Here, we propose such an experimental setup, in which a twisted hand is diagonally viewed from behind, which is called a "monkey's hand." Although the subject cannot see the thumb hidden behind his or her arm, he or she feels that the monkey's hand has an ambiguous thumb that functionally never exists but structurally exists. This ambiguity is consistent with experimental results on proprioceptive drift, by which the deformation of the hand is measured. The ambiguity of the presence and absence of the thumb is finally analyzed with a specific algebraic structure called a lattice. This can help us understand disownership as being different from the absence of ownership.

How do soldier crabs behave when seeing vibrating robots?

Metaheuristic algorithms are a method of searching for a suboptimal solution and are implemented by a large number of agents, such as a swarm of animals. In this method, it is very important to adjust the relationships and/or interplay between individual freedoms and constraints as a group. The phenomena related to this interplay are strongly relevant for self-organized criticality showing a power law distribution. Since individuals' independent behavior and translation as a group coexist in a swarm of soldier crabs, we conducted an experiment involving soldier crabs to estimate whether a power law distribution results from that interplay. The engine of translation was implemented by the directed movement of robot crabs. Soldier crabs confronting moving robot crabs were observed in the experiment. Here, we show that the interaction between robots and soldier crabs entails a Lévy walk characterized by a power law distribution of step length as well as the real swarm. This result suggests that soldier crabs could be attracted by the directed motion of robots and that combining a random walk with ballistic movement can realize a Lévy walk.

Connecting the free energy principle with quantum cognition.

It appears that the free energy minimization principle conflicts with quantum cognition since the former adheres to a restricted view based on experience while the latter allows deviations from such a restricted view. While free energy minimization, which incorporates Bayesian inference, leads to a Boolean lattice of propositions (classical logic), quantum cognition, which seems to be very dissimilar to Bayesian inference, leads to an orthomodular lattice of propositions (quantum logic). Thus, we address this challenging issue to bridge and connect the free energy minimization principle with the theory of quantum cognition. In this work, we introduce "excess Bayesian inference" and show that this excess Bayesian inference entails an underlying orthomodular lattice, while classic Bayesian inference entails a Boolean lattice. Excess Bayesian inference is implemented by extending the key idea of Bayesian inference beyond classic Bayesian inference and its variations. It is constructed by enhancing the idea of active inference and/or embodied intelligence. The appropriate lattice structure of its logic is obtained from a binary relation transformed from a distribution of the joint probabilities of data and hypotheses by employing a rough-set lattice technique in accordance with quantum cognition logic.

Psychological origin of quantum logic: An orthomodular lattice derived from natural-born intelligence without Hilbert space.

While the role of quantum theory becomes increasingly important through molecular computing and quantum cognition, it is still unclear how quantum mechanics can be involved in macroscopic phenomena. We previously argued the origin of quantum logic in terms of lattice theory; however, we do not refer to Hilbert space very much. Here, we show the psychological origin of quantum logic (i.e., orthomodular lattice) by not using Hilbert space. After showing how Hilbert space plays a role in constructing an orthomodular lattice, we show the idea of natural-born intelligence, in which a binary opposition pair can constitute not only positive but negative antinomy. In taking an object outside and an image inside a brain as that binary opposition pair, the structure entailing positive and negative antinomy is expressed as a specific binary relation consisting of multiple diagonal relations, which is called traumatic relation. Finally, we show that the traumatic relation leads to an orthomodular lattice without Hilbert space.

Computational Power of Asynchronously Tuned Automata Enhancing the Unfolded Edge of Chaos.

Asynchronously tuned elementary cellular automata (AT-ECA) are described with respect to the relationship between active and passive updating, and that spells out the relationship between synchronous and asynchronous updating. Mutual tuning between synchronous and asynchronous updating can be interpreted as the model for dissipative structure, and that can reveal the critical property in the phase transition from order to chaos. Since asynchronous tuning easily makes behavior at the edge of chaos, the property of AT-ECA is called the unfolded edge of chaos. The computational power of AT-ECA is evaluated by the quantitative measure of computational universality and efficiency. It shows that the computational efficiency of AT-ECA is much higher than that of synchronous ECA and asynchronous ECA.

Effect of Hidden Vector on the Speech of PRVA.

This study aimed to propose a novel method for designing a product recommendation virtual agent (PRVA) that can keep users motivated to interact with the agent. In prior papers, many methods of keeping users motivated postulated real-time and multi-modal interactions. The proposed novel method can be used in one-direction interaction. We defined the notion of the "hidden vector," that is, information that is not mentioned by a PRVA and that the user can suppose spontaneously. We conducted an experiment to verify the hypothesis that PRVAs having a hidden vector are more effective than other PRVAs. As a result, it was shown that PRVAs having a hidden vector were perceived as being more persuasive than other PRVAs and strongly motivated the users to use the PRVAs. From these results, the proposed method was shown to be effective.

Lévy Walk in Swarm Models Based on Bayesian and Inverse Bayesian Inference.

While swarming behavior is regarded as a critical phenomenon in phase transition and frequently shows the properties of a critical state such as Lévy walk, a general mechanism to explain the critical property in swarming behavior has not yet been found. Here, we address this problem with a simple swarm model, the Self-Propelled Particle (SPP) model, and propose a way to explain this critical behavior by introducing agents making decisions via the data-hypothesis interaction in Bayesian inference, namely, Bayesian and inverse Bayesian inference (BIB). We compare three SPP models, namely, the simple SPP, the SPP with Bayesian-only inference (BO) and the SPP with BIB models. We show that only the BIB model entails coexisting tornado, splash and translation behaviors, and the Lévy walk pattern.

Analysis and synthesis of a growing network model generating dense scale-free networks via category theory.

We propose a growing network model that can generate dense scale-free networks with an almost neutral degree-degree correlation and a negative scaling of local clustering coefficient. The model is obtained by modifying an existing model in the literature that can also generate dense scale-free networks but with a different higher-order network structure. The modification is mediated by category theory. Category theory can identify a duality structure hidden in the previous model. The proposed model is built so that the identified duality is preserved. This work is a novel application of category theory for designing a network model focusing on a universal algebraic structure.

Breaking of the Trade-Off Principle between Computational Universality and Efficiency by Asynchronous Updating.

Although natural and bioinspired computing has developed significantly, the relationship between the computational universality and efficiency beyond the Turing machine has not been studied in detail. Here, we investigate how asynchronous updating can contribute to the universal and efficient computation in cellular automata (CA). First, we define the computational universality and efficiency in CA and show that there is a trade-off relation between the universality and efficiency in CA implemented in synchronous updating. Second, we introduce asynchronous updating in CA and show that asynchronous updating can break the trade-off found in synchronous updating. Our finding spells out the significance of asynchronous updating or the timing of computation in robust and efficient computation.

Virtual Hand with Ambiguous Movement between the Self and Other Origin: Sense of Ownership and 'Other-Produced' Agency.

The feeling that a body part is one's own body (sense of ownership; SoO) and the feeling based on the causal relationship between one's will and action (sense of agency; SoA) have been recognized as the basis of our bodily self-consciousness. Previously, the illusory SoO over a fake body part (e.g., rubber hand) was introduced as the rubber hand illusion (RHI). Furthermore, it was determined that one could also evoke a SoA over an object with movements linked to the one's prior intention. On the other hand, the postdictivity of our spontaneity implies that it is essentially inseparable whether actions originate from self or others. In other words, our SoA or daily experiences are obtained in such as inseparable scenario. Previous research, however, has maintained the premise that self- and other-origin movements are perceptually distinguishable. Here, we implement a protocol to make these aspects ambiguous for the participants and to estimate whether they can feel SoO and/or SoA and how. To this end, we employ an experiment using virtual reality, under which participants observe virtual fingers moving very slowly (or quickly or not moving) while their own fingers do not move. For evaluation of the illusory SoO, measurements of skin conductance responses against a knife threat are adopted. Additionally, we introduce face-to-face interviews to determine whether the feelings regarding the slow movement match the conventional SoA definition. Our representative results suggest that the SoO is evoked over the hand, and various attitudes to accept its movement as the participant's own with awareness that they did not originate it are reported by the majority. As the results show, the novelty of this protocol is discovering that in such a situation, the SoO cooperates with an externally produced SoA to establish one's own bodily experience rather than the independence of the SoO and SoA.

Three types of logical structure resulting from the trilemma of free will, determinism and locality.

How can one defend free will against determinism? Since quantum mechanics entails non-locality, it enables the co-existence of free will and determinism. Is non-locality in cognition possible, or must quantum mechanics be rejected? Here, we define free will, determinism and locality in terms of a binary relation between objects and representations, and we verify that the three concepts constitute a trilemma. We also show that non-locality in cognition is naturally found in decision making without any assumption of quantum mechanics. Three kinds of relations result from the trilemma. By using a rough set lattice technique, the three kinds of relations can be transformed into three kinds of logical structures. Type I is a naive set theoretical logic or Boolean algebra (i.e., all possible combinations of binary yes-no responses). Type II comprises all possible combinations of various multiple values, such as for the symptoms of schizophrenia. Type III is a non-local disjoint union of multiple contexts. The type III structure can show how non-locality in cognition can lead to the co-existence of free will and determinism. Loss of non-locality could play an essential role in the malfunction of the separation and integration of the self and others.

A new method of Bayesian causal inference in non-stationary environments.

Bayesian inference is the process of narrowing down the hypotheses (causes) to the one that best explains the observational data (effects). To accurately estimate a cause, a considerable amount of data is required to be observed for as long as possible. However, the object of inference is not always constant. In this case, a method such as exponential moving average (EMA) with a discounting rate is used to improve the ability to respond to a sudden change; it is also necessary to increase the discounting rate. That is, a trade-off is established in which the followability is improved by increasing the discounting rate, but the accuracy is reduced. Here, we propose an extended Bayesian inference (EBI), wherein human-like causal inference is incorporated. We show that both the learning and forgetting effects are introduced into Bayesian inference by incorporating the causal inference. We evaluate the estimation performance of the EBI through the learning task of a dynamically changing Gaussian mixture model. In the evaluation, the EBI performance is compared with those of the EMA and a sequential discounting expectation-maximization algorithm. The EBI was shown to modify the trade-off observed in the EMA.

Propagating wave based on transition of interaction within animal group.

Propagating waves, information transfers of direction of travel in collective groups, have been observed in animal groups of insects, birds, fish, and mammals. Nevertheless, although many previously proposed models of group behaviors have elucidated various aspects of collective motion, none has directly shown the propagating wave constructively. These models consisted of flocking algorithms in which individuals modify their positions or velocities through average responses to their neighbors. The algorithms involve the function of diluting local fluctuations, individual motions, or social cues that initiate coherent decision-making of where to travel and which spread through a group in the form of a wave. The present study challenged physics-inspired models based solely on average interaction and instead proposed a combination with pair interaction: the 'copy' mechanism. By the mechanism, individuals specially attend and mimic the motion of the largest turning neighbor. The model comprises three modes (base, copy, and align modes) that sequentially switch among themselves, depending on the degree of variance in direction. The model therefore involves propagating waves that produce rapid collective responses and quick turning motions of a group. This proposal is an attempt to uncover the mechanisms of self-organized waves in simulation studies of coordinated groups, without explicit signals such as alarm calls. Understanding such mechanisms is expected to contribute to the 'collective mind' metaphor, answering the question of how animal groups obtain higher-order computational capabilities from local inter-individual interactions.

Ordinal Preferential Attachment: A Self-Organizing Principle Generating Dense Scale-Free Networks.

Networks are useful representations for analyzing and modeling real-world complex systems. They are often both scale-free and dense: their degree distribution follows a power-law and their average degree grows over time. So far, it has been argued that producing such networks is difficult without externally imposing a suitable cutoff for the scale-free regime. Here, we propose a new growing network model that produces dense scale-free networks with dynamically generated cutoffs. The link formation rule is based on a weak form of preferential attachment depending only on order relations between the degrees of nodes. By this mechanism, our model yields scale-free networks whose scaling exponents can take arbitrary values greater than 1. In particular, the resulting networks are dense when scaling exponents are 2 or less. We analytically study network properties such as the degree distribution, the degree correlation function, and the local clustering coefficient. All analytical calculations are in good agreement with numerical simulations. These results show that both sparse and dense scale-free networks can emerge through the same self-organizing process.

Observing the Transformation of Bodily Self-consciousness in the Squeeze-machine Experiment.

How is our bodily self-consciousness acquired, and how does it affect cognition? To investigate this, we conducted an experiment using the squeeze machine, a device that provides pressure along the length of the user's whole body. The squeeze machine is used to help autistic people relax. The inventor of the machine, Dr. Temple Grandin says that the squeeze machine, beyond bringing her relaxation, enables her to feel empathy for others. This claim is of considerable interest and raises the following two points; first, the problem of empathy in autism is an important issue and Squeeze Machine could be effective. Second, it suggests that the physical action of Squeeze Machine could provide an insight of mind-body problem to us. Here, we hypothesize that the squeeze machine focuses conscious to direct the bodily self, transforming bodily self-consciousness itself. Such intentionality could bring empathy to others. In this study, we tested whether bodily self-consciousness would be transformed through the squeeze-machine experience. In the first part of the protocol, we simplified the original design of Grandin's squeeze machine but ensured that it retained its relaxing effect. In the second part of the protocol, we adopted a preestablished method of peri-personal space (PPS) measurement to estimate changes in extended bodily space. The results showed that the boundaries of PPS that appeared in the control experiment disappeared during the use of the squeeze machine. Indeed, collected subjective reports suggest that bodily self-consciousness continually drifted between the point of action of the external force (squeeze-machine pressure) and of an internal force (balance among body parts that are usually not consciously controlled), leading to the abandonment of the immobilization of individual PPS.

Inverse Bayesian inference in swarming behaviour of soldier crabs.

Animals making a group sometimes approach and sometimes avoid a dense area of group mates, and that reveals the ambiguity of density preference. Although the ambiguity is not expressed by a simple deterministic local rule, it seems to be implemented by probabilistic inference that is based on Bayesian and inverse Bayesian inference. In particular, the inverse Bayesian process refers to perpetual changing of hypotheses. We here analyse a time series of swarming soldier crabs and show that they are employed to Bayesian and inverse Bayesian inference. Comparing simulation results with data of the real swarm, we show that the interpretation of the movement of soldier crabs which can be based on the inference can lead to the identification of a drastic phase shift-like transition of gathering and dispersing.This article is part of the theme issue 'Dissipative structures in matter out of equilibrium: from chemistry, photonics and biology (part 2)'.

Embryogenic remodeling of global chromatin and its role on structure of corresponding lattice representation.

Recent findings demonstrate that chromatin is functionally compartmentalized and packed into three dimensional multi-hierarchical structures that influence gene expression patterns. Using lattice theory tools we compare lattice representation of unstructured DNA, as identified in early-embryo phase, with compartmentalized DNA, as found in later embryo phases and in differentiated cells. By comparing these two representations we show that corresponding contact maps have elementary diagonal structure (unstructured DNA) and block diagonal structure (compartmentalized DNA). We show that a lattice corresponding to the binary relation with block diagonal structure is a product of so called Chinese lantern lattice. In contrast to Boolean lattice, formation of words in Chinese lantern lattice is highly restricted which is comparable to emergence of DNA compartmentalization during embryogenesis.

Optimal random search using limited spatial memory.

Lévy walks are known to be efficient movements because Lévy walkers search wide areas while restricting returns to previously visited sites. A self-avoiding walk (SAW) is a series of moves on a lattice that visit the same place only once. As such, SAWs can also be effective search algorithms. However, it is not realistic that foragers memorize many visited positions for a long time. In this work, we investigated whether foragers performed optimal searches when having limited memory. The agent in our model followed SAWs to some extent by memorizing and avoiding visited places. However, the agent lost its memory after a while. In that situation, the agent changed its reactions to visited patches by considering global trail patterns based on local memorized information. As a result, we succeeded in making the agent occasionally produce ballistic walks related to power-law tailed movements across some ranges.

Modeling of decision-making process for moving straight using inverse Bayesian inference.

Humans sometimes make unreasonable decisions when viewed in objective terms. Even in the real world, we may lose sense of direction by turning around the corner several times or mistaking the estimation of travel distance. We experimented in virtual space how we lose sense of direction under what circumstances. In the experiment, subjects viewed a three-dimensional space displayed on a computer display in the first person's perspective and were instructed to go straight from the start to the goal position. Results showed that unreasonable selections that strayed from the centerline connecting the start and goal positions were frequently made. The change in the direction is more influential than the change in the distance, and the angle of turning also affects. Furthermore, the subject's decision - making process was modeled using Bayesian inference and inverse Bayesian inference. Comparing the two models, when the decision-making pattern suddenly changed, the model by inverse Bayesian inference could follow up faster than the Bayesian inference.