A novel plasticity rule can explain the development of sensorimotor intelligence

Grounding autonomous behavior in the nervous system is a fundamental challenge for neuroscience. In particular, the self-organized behavioral development provides more questions than answers. Are there special functional units for curiosity, motivation, and creativity? This paper argues that these features can be grounded in synaptic plasticity itself, without requiring any higher level constructs. We propose differential extrinsic plasticity (DEP) as a new synaptic rule for self-learning systems and apply it to a number of complex robotic systems as a test case. Without specifying any purpose or goal, seemingly purposeful and adaptive behavior is developed, displaying a certain level of sensorimotor intelligence. These surprising results require no system specific modifications of the DEP rule but arise rather from the underlying mechanism of spontaneous symmetry breaking due to the tight brain-body-environment coupling. The new synaptic rule is biologically plausible and it would be an interesting target for a neurobiolocal investigation. We also argue that this neuronal mechanism may have been a catalyst in natural evolution.Comment: 18 pages, 5 figures, 7 video

Contestable adulthood: variability and disparity in markers for negotiating the transition to adulthood

Recent research has identified a discreet set of subjective markers that are seen as characterizing the transition to adulthood. The current study challenges this coherence by examining the disparity and variability in young people’s selection of such criteria. Four sentence-completion cues corresponding to four differentcontexts in which adult status might be contested were given to 156 British 16- to 17-year-olds. Their qualitative responses were analyzed to explore patterns whilst capturing some of their richness and diversity. An astonishing amount of variability emerged, both within and between cued contexts.The implications of this variability for how the transition to adulthood is experienced are explored. The argument is made that markers of the transition to adulthood are not merely reflective of the bio–psycho–social development of young people. Rather, adulthood here is seen as an essentially contested concept,located within the discursive interactional environment in which young people participate

Interpretable multiclass classification by MDL-based rule lists

Interpretable classifiers have recently witnessed an increase in attention from the data mining community because they are inherently easier to understand and explain than their more complex counterparts. Examples of interpretable classification models include decision trees, rule sets, and rule lists. Learning such models often involves optimizing hyperparameters, which typically requires substantial amounts of data and may result in relatively large models. In this paper, we consider the problem of learning compact yet accurate probabilistic rule lists for multiclass classification. Specifically, we propose a novel formalization based on probabilistic rule lists and the minimum description length (MDL) principle. This results in virtually parameter-free model selection that naturally allows to trade-off model complexity with goodness of fit, by which overfitting and the need for hyperparameter tuning are effectively avoided. Finally, we introduce the Classy algorithm, which greedily finds rule lists according to the proposed criterion. We empirically demonstrate that Classy selects small probabilistic rule lists that outperform state-of-the-art classifiers when it comes to the combination of predictive performance and interpretability. We show that Classy is insensitive to its only parameter, i.e., the candidate set, and that compression on the training set correlates with classification performance, validating our MDL-based selection criterion

Outer-totalistic cellular automata on graphs

We present an intuitive formalism for implementing cellular automata on arbitrary topologies. By that means, we identify a symmetry operation in the class of elementary cellular automata. Moreover, we determine the subset of topologically sensitive elementary cellular automata and find that the overall number of complex patterns decreases under increasing neighborhood size in regular graphs. As exemplary applications, we apply the formalism to complex networks and compare the potential of scale-free graphs and metabolic networks to generate complex dynamics.Comment: 5 pages, 4 figures, 1 table. To appear in Physics Letters

MODERATE SEVERITY DISTURBANCE HAS SIMILAR EFFECTS ON THE PRODUCTION OF THREE FORESTS NESTED WITHIN THE UPPER GREAT LAKES LANDSCAPE

Moderate severity disturbances, which only kill a subset of canopy trees (e.g., via insects, pathogens, and windthrow), are increasingly widespread, and can alter forest structure and production. Whether moderate severity disturbance similarly affects the net primary production (NPP) of different forest stands within inherently heterogeneous landscapes, however, is unknown. We experimentally disturbed three, 2-ha stands varying in forest structure and primary production, reducing stand basal area 38 to 66 % by stem girdling all mature early successional aspen (Populus) and birch (Betula). For nearly a decade, we examined how the forest stands restructured and recovered, and linked post-recovery physical and biological structure with light absorption and wood NPP. Disturbance significantly altered the structure of all stands and prompted a similar decade-long pattern of primary production decline and recovery. All stands exhibited an initial reduction in wood NPP, recovering to, or exceeded pre-disturbance levels within eight years. Following the recovery of wood NPP, more biologically diverse forest canopies with higher leaf area indexes captured more light, and, subsequently, had higher rates of wood NPP. We provide limited support that disturbance may enhance long-term primary production through its effects on canopy structural reorganization. We conclude that, while the forests examined responded similarly to disturbance, improved understanding of different forest ecosystems’ response to disturbance remains critical to informing carbon management decisions across diverse landscape mosaics