The Role of Membrane Trafficking in G Protein-Coupled Receptor Regulation

Movements of a receptor in the plasma membrane and within the cell influence receptor function and physiology. I have investigated the role of such movements, generally known as membrane trafficking, in G protein-coupled receptor regulation. My studies show that agonist-promoted internalization and postendocytic sorting determine the degree of resensitization of opioid m (MOR) and d (DOR) receptors, and dopamine D2 (D2R) receptors. Further, postendocytic sorting of DOR and D2R is determined by the non-covalent interaction of the receptors with the protein G protein-coupled associated sorting protein (GASP). Abrogation of the DOR- and D2R-GASP interaction leads to an altered postendocytic fate of the two receptors and results in their recycling and resensitization. I have also shown that the cognate agonist des-Arg10-kallidin for the G protein-coupled bradykinin B1 receptor (B1R) acts as an inverse agonist on receptor endocytosis and does not cause receptor desensitization. Further, I have mapped the internalization routes utilized by the B1R and bradykinin B2 receptors and isolated the domains necessary for their internalization and postendocytic sorting. In summary, my studies highlight and detail a novel regulatory mode of activity in three receptor groups of great physiological and pharmacological significance in areas such as pain transmission. Further, I show that receptor membrane trafficking can be artificially modulated to impact in vivo receptor function. Thus, my result may be directly utilized for future therapeutic purposes

Memory for Stimulus Sequences: a Divide between Humans and Other Animals?

Humans stand out among animals for their unique capacities in domains such as language, culture and imitation, yet it has been difficult to identify cognitive elements that are specifically human. Most research has focused on how information is processed after it is acquired, e.g. in problem solving or ‘insight’ tasks, but we may also look for species differences in the initial acquisition and coding of information. Here, we show that non-human species have only a limited capacity to discriminate ordered sequences of stimuli. Collating data from 108 experiments on stimulus sequence discrimination (1540 data points from 14 bird and mammal species), we demonstrate pervasive and systematic errors, such as confusing a red–green sequence of lights with green–red and green–green sequences. These errors can persist after thousands of learning trials in tasks that humans learn to near perfection within tens of trials. To elucidate the causes of such poor performance, we formulate and test a mathematical model of non-human sequence discrimination, assuming that animals represent sequences as unstructured collections of memory traces. This representation carries only approximate information about stimulus duration, recency, order and frequency, yet our model predicts non-human performance with a 5.9% mean absolute error across 68 datasets. Because human-level cognition requires more accurate encoding of sequential information than afforded by memory traces, we conclude that improved coding of sequential information is a key cognitiv

The Power of Associative Learning and The Ontogeny of Optimal Behaviour

Behaving efficiently (optimally or near-optimally) is central to animals’ adaptation to their environment. Much evolutionary biology assumes, implicitly or explicitly, that optimal behavioural strategies are genetically inherited, yet the behaviour of many animals depends crucially on learning. The question of how learning contributes to optimal behaviour is largely open. Here we propose an associative learning model that can learn optimal behaviour in a wide variety of ecologically relevant circumstances. The model learns through chaining, a term introduced by Skinner to indicate learning of behaviour sequences by linking together shorter sequences or single behaviours. Our model formalizes the concept of conditioned reinforcement (the learning process that underlies chaining) and is closely related to optimization algorithms from machine learning. Our analysis dispels the common belief that associative learning is too limited to produce ‘intelligent’ behaviour such as tool use, social learning, selfcontrol or expectations of the future. Furthermore, the model readily accounts for both instinctual and learned aspects of behaviour, clarifying how genetic evolution and individual learning complement each other, and bridging a long-standing divide between ethology and psychology. We conclude that associative learning, supported by genetic predispositions and including the oft-neglected phenomenon of conditioned reinforcement, may suffice to explain the ontogeny of optimal behaviour in most, if not all, non-human animals. Our results establish associative learning as a more powerful optimizing mechanism than acknowledged by current opinion

Social learning through associative processes: a computational theory

Social transmission of information is a key phenomenon in the evolution of behaviour and in the establishment of traditions and culture. The diversity of social learning phenomena has engendered a diverse terminology and numerous ideas about underlying learning mechanisms, at the same time that some researchers have called for a unitary analysis of social learning in terms of associative processes. Leveraging previous attempts and a recent computational formulation of associative learning, we analyse the following learning scenarios in some generality: learning responses to social stimuli, including learning to imitate; learning responses to non-social stimuli; learning sequences of actions; learning to avoid danger. We conceptualize social learning as situations in which stimuli that arise from other individuals have an important role in learning. This role is supported by genetic predispositions that either cause responses to social stimuli or enable social stimuli to reinforce specific responses. Simulations were performed using a new learning simulator program. The simulator is publicly available and can be used for further theoretical investigations and to guide empirical research of learning and behaviour. Our explorations show that, when guided by genetic predispositions, associative processes can give rise to a wide variety of social learning phenomena, such as stimulus and local enhancement, contextual imitation and simple production imitation, observational conditioning, and social and response facilitation. In addition, we clarify how associative mechanisms can result in transfer of information and behaviour from experienced to naive individuals

All Aboard: ERP Implementation as Participatory Design

Following a previous description of Enterprise Resource Planning (ERP) implementations as participatory design (Pries-Heje & Dittrich, 2009), this paper explores the case of a medium-sized, family-owned manufacturing company and its endeavors with changing their current ERP system. The case was selected on the premise of it being perceived a success by the involved stakeholders. Through a series of interviews and analysis of secondary material, the case covers the period between 1995 and 2010. As the results show, several instances of user involvement and participation can be found throughout the case. According to the respondents, this is seen as one of the central elements of the success. This is discussed in relation to previous findings and a call for future research into ERP implementation is presented

Models of conditioned reinforcement and abnormal behaviour in captive animals

Abnormal behaviours are common in captive animals, and despite a lot of research, the development, maintenance and alleviation of these behaviours are not fully understood. Here, we suggest that conditioned reinforcement can induce sequential dependencies in behaviour that are difficult to infer from direct observation. We develop this hypothesis using recent models of associative learning that include conditioned reinforcement and inborn facets of behaviour, such as predisposed responses and motivational systems. We explore three scenarios in which abnormal behaviour emerges from a combination of associative learning and a mismatch between the captive environment and inborn predispositions. The first model considers how abnormal behaviours, such as locomotor stereotypies, may arise from certain spatial locations acquiring conditioned reinforcement value. The second model shows that conditioned reinforcement can give rise to abnormal behaviour in response to stimuli that regularly precede food or other reinforcers. The third model shows that abnormal behaviour can result from motivational systems being adapted to natural environments that have different temporal structures than the captive environment. We conclude that models including conditioned reinforcement offer an important theoretical insight regarding the complex relationships between captive environments, inborn predispositions, and learning. In the future, this general framework could allow us to further understand and possibly alleviate abnormal behaviours

The Number of Cultural Traits Is Correlated with Female Group Size but Not with Male Group Size in Chimpanzee Communities

What determines the number of cultural traits present in chimpanzee (Pan troglodytes) communities is poorly understood. In humans, theoretical models suggest that the frequency of cultural traits can be predicted by population size. In chimpanzees, however, females seem to have a particularly important role as cultural carriers. Female chimpanzees use tools more frequently than males. They also spend more time with their young, skewing the infants' potential for social learning towards their mothers. In Gombe, termite fishing has been shown to be transmitted from mother to offspring. Lastly, it is female chimpanzees that transfer between communities and thus have the possibility of bringing in novel cultural traits from other communities. From these observations we predicted that females are more important cultural carriers than males. Here we show that the reported number of cultural traits in chimpanzee communities correlates with the number of females in chimpanzee communities, but not with the number of males. Hence, our results suggest that females are the carriers of chimpanzee culture

The global biogeography of tree leaf form and habit

Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17–34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling

Integrated global assessment of the natural forest carbon potential

Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system 1. Remote-sensing estimates to quantify carbon losses from global forests 2–5 are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced 6 and satellite-derived approaches 2,7,8 to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151–363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea 2,3,9 that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets