Synchronisation effects on the behavioural performance and information dynamics of a simulated minimally cognitive robotic agent

Oscillatory activity is ubiquitous in nervous systems, with solid evidence that synchronisation mechanisms underpin cognitive processes. Nevertheless, its informational content and relationship with behaviour are still to be fully understood. In addition, cognitive systems cannot be properly appreciated without taking into account brain–body– environment interactions. In this paper, we developed a model based on the Kuramoto Model of coupled phase oscillators to explore the role of neural synchronisation in the performance of a simulated robotic agent in two different minimally cognitive tasks. We show that there is a statistically significant difference in performance and evolvability depending on the synchronisation regime of the network. In both tasks, a combination of information flow and dynamical analyses show that networks with a definite, but not too strong, propensity for synchronisation are more able to reconfigure, to organise themselves functionally and to adapt to different behavioural conditions. The results highlight the asymmetry of information flow and its behavioural correspondence. Importantly, it also shows that neural synchronisation dynamics, when suitably flexible and reconfigurable, can generate minimally cognitive embodied behaviour

Modeling co-operative volume signaling in a plexus of nitric oxide synthase-expressing neurons

In vertebrate and invertebrate brains, nitric oxide (NO) synthase (NOS) is frequently expressed in extensive meshworks (plexuses) of exceedingly fine fibers. In this paper, we investigate the functional implications of this morphology by modeling NO diffusion in fiber systems of varying fineness and dispersal. Because size severely limits the signaling ability of an NO-producing fiber, the predominance of fine fibers seems paradoxical. Our modeling reveals, however, that cooperation between many fibers of low individual efficacy can generate an extensive and strong volume signal. Importantly, the signal produced by such a system of cooperating dispersed fibers is significantly more homogeneous in both space and time than that produced by fewer larger sources. Signals generated by plexuses of fine fibers are also better centered on the active region and less dependent on their particular branching morphology. We conclude that an ultrafine plexus is configured to target a volume of the brain with a homogeneous volume signal. Moreover, by translating only persistent regional activity into an effective NO volume signal, dispersed sources integrate neural activity over both space and time. In the mammalian cerebral cortex, for example, the NOS plexus would preferentially translate persistent regional increases in neural activity into a signal that targets blood vessels residing in the same region of the cortex, resulting in an increased regional blood flow. We propose that the fineness-dependent properties of volume signals may in part account for the presence of similar NOS plexus morphologies in distantly related animals

A miniature UV-VIS spectrometer for the surface of Mars

A miniature spectrometer is in the process of development for a future Mars mission, to measure the UV-VIS spectrum encountered at the martian surface. With an intended mass of ~100 g, the spectrometer is planned as part of the ESA ExoMars mission

The view from elsewhere: perspectives on ALife Modeling

Many artificial life researchers stress the interdisciplinary character of the field. Against such a backdrop, this report reviews and discusses artificial life, as it is depicted in, and as it interfaces with, adjacent disciplines (in particular, philosophy, biology, and linguistics), and in the light of a specific historical example of interdisciplinary research (namely cybernetics) with which artificial life shares many features. This report grew out of a workshop held at the Sixth European Conference on Artificial Life in Prague and features individual contributions from the workshop's eight speakers, plus a section designed to reflect the debates that took place during the workshop's discussion sessions. The major theme that emerged during these sessions was the identity and status of artificial life as a scientific endeavor

Individual differences in sharing false political information on social media: deliberate and accidental sharing, motivations and positive schizotypy

False political information – misinformation or disinformation - is widely spread on social media. Individual social media users play a large part in this. However, only a minority actively share false material. It is important to establish what sets these individuals apart from those who do not, and why they do it. Motivations for sharing may vary and are likely to differ between people who share false material unknowingly and on purpose. In this paper we consider the extent to which individual differences in personality and other variables, and motivations for sharing, are associated with the likelihood of people sharing false political information both accidentally and deliberately. In a series of four studies (Ns=614, 563, 627, 113) we examined predictors of sharing false political information using different methodological approaches. Across the four studies, a key finding was that positive schizotypy is associated with measures of sharing false information both accidentally and deliberately. Motivations for sharing political information online were also relevant, with sharing for reasons of 'raising awareness' appearing particularly important. Implications for research and practice are discussed

Transmit Antenna Selection for Massive MIMO Systems

In this paper, particle swarm optimization is employed to carry out transmit antenna subgrouping algorithm for massive multiple input and multiple output (MIMO) system. A minimum number of transmit antenna elements are selected to achieve a similar quality of service (QoS) as that of a single user MIMO system. Simulation results show that our proposed algorithm achieves similar capacity performance as compared to massive MIMO systems when employing exhaustive search for transmit antenna selection

Chaotic exploration and learning of locomotion behaviours

We present a general and fully dynamic neural system, which exploits intrinsic chaotic dynamics, for the real-time goal-directed exploration and learning of the possible locomotion patterns of an articulated robot of an arbitrary morphology in an unknown environment. The controller is modeled as a network of neural oscillators that are initially coupled only through physical embodiment, and goal-directed exploration of coordinated motor patterns is achieved by chaotic search using adaptive bifurcation. The phase space of the indirectly coupled neural-body-environment system contains multiple transient or permanent self-organized dynamics, each of which is a candidate for a locomotion behavior. The adaptive bifurcation enables the system orbit to wander through various phase-coordinated states, using its intrinsic chaotic dynamics as a driving force, and stabilizes on to one of the states matching the given goal criteria. In order to improve the sustainability of useful transient patterns, sensory homeostasis has been introduced, which results in an increased diversity of motor outputs, thus achieving multiscale exploration. A rhythmic pattern discovered by this process is memorized and sustained by changing the wiring between initially disconnected oscillators using an adaptive synchronization method. Our results show that the novel neurorobotic system is able to create and learn multiple locomotion behaviors for a wide range of body configurations and physical environments and can readapt in realtime after sustaining damage

Predictive validity of the UK clinical aptitude test in the final years of medical school:a prospective cohort study

Peer reviewedPublisher PD

The influence of neighborhood characteristics on police officers\u27 encounters with persons suspected to have a serious mental illness

Objective: Police officers\u27 decisions and behaviors are impacted by the neighborhood context in which police encounters occur. For example, officers may use greater force and be more likely to make arrests in disadvantaged neighborhoods. We examined whether neighborhood characteristics influence police encounters with individuals suspected to have a serious mental illness, addictive disorder, or developmental disability. Method: We obtained data on 916 encounters from 166 officers in six jurisdictions in Georgia, USA and abstracted geographical data pertaining to the location of these encounters from United States Decennial Census data. Encounters were nested within 163 census tracts. Officer-reported data covered general encounter characteristics, the officer\u27s perception of the subject\u27s condition, subject demographics, use of force, and disposition of the encounter (e.g., arrest v. referral or transport to treatment services). Geographical data included 17 variables representing population and housing characteristics of the census tracts, from which three indices pertaining to neighborhood income, stability, and immigration status were derived using factor-analytic techniques. We then examined associations of these indices with various encounter-related variables using multi-level analysis. Results: Encounters taking place in higher-income and higher-stability census tracts were more likely to be dispatch-initiated and take place in a private home compared to those in lower-income and lower-stability neighborhoods. In higher-income neighborhoods, encounters were more likely to involve a subject suspected to have a mental illness (as opposed to an addictive disorder or developmental disability) and less likely to involve a subject suspected to have alcohol problems. The officer\u27s level of force used was not associated with neighborhood factors. Regarding disposition, although the likelihood of arrest was unrelated to neighborhood characteristics, encounters taking place in higher-immigrant neighborhoods were more likely to result in referral or transport to services than those in lower-immigrant neighborhoods. Conclusion: Neighborhood characteristics are important to consider in research on police interactions with individuals with serious mental illnesses, addictive disorders, or developmental disabilities. Such research could inform departmental training policies and procedures based on the needs of the jurisdictions served. (C) 2014 Elsevier Ltd. All rights reserved