Navigating ‘taxation’ on the Congo River: the interplay of legitimation and ‘officialisation’

Based on comprehensive research among boat operators and navy personnel working on the Congo River (DRC), this article explores how assessments of ‘taxation’ are shaped by the interplay of legitimation and ‘officialisation’. As such, it draws upon and contributes to scholarly debates on taxpayers’ attitudes towards taxation. While boat operators resent having to pay a plethora of authorities, including the navy, along the Congo River, the article demonstrates how they locate these ‘taxes’ on a spectrum from more to less legitimate. These assessments are shaped by various factors: authorities’ legitimacy as ‘measured’ by their official mandate and importance; public and non-official service provision; and the deployment of symbols of ‘stateness’. In interaction, these factors legitimise and ‘officialise’ ‘taxes’ by the navy that are prohibited in legislation. These findings caution against the a priori use of the labels ‘official’ and ‘non-official’, emphasising the need to better grasp these notions’ emic understandings

Gated communities: Definitions, causes and consequences

Gated communities became an 'object of study' in the 1990s as social scientists observed their growth in several cities; they are now a feature of the urban landscape in most cities around the world. The expansion of gated communities has led to prolific research, examining different aspects of this type of residential development and providing evidence from case studies worldwide. This paper reviews how gated communities are conceptualised according to the literature and identifies the main factors influencing their development. It also considers spatial, economic, political and social consequences of the development of gated communities. These elements should be taken into account by planners and policymakers to minimise their negative impacts and maximise the positive consequences of a residential option that is likely to be part of the urban landscape for a long time

Expression of CXCL10 is associated with response to radiotherapy and overall survival in squamous cell carcinoma of the tongue

Five-year survival for patients with oral cancer has been disappointingly stable during the last decades, creating a demand for new biomarkers and treatment targets. Lately, much focus has been set on immunomodulation as a possible treatment or an adjuvant increasing sensitivity to conventional treatments. The objective of this study was to evaluate the prognostic importance of response to radiotherapy in tongue carcinoma patients as well as the expression of the CXC-chemokines in correlation to radiation response in the same group of tumours. Thirty-eight patients with tongue carcinoma that had received radiotherapy followed by surgery were included. The prognostic impact of pathological response to radiotherapy, N-status, T-stage, age and gender was evaluated using Cox's regression models, Kaplan-Meier survival curves and chi-square test. The expression of 23 CXC-chemokine ligands and their receptors were evaluated in all patients using microarray and qPCR and correlated with response to treatment using logistic regression. Pathological response to radiotherapy was independently associated to overall survival with a 2-year survival probability of 81 % for patients showing a complete pathological response, while patients with a non-complete response only had a probability of 42 % to survive for 2 years (p = 0.016). The expression of one CXC-chemokine, CXCL10, was significantly associated with response to radiotherapy and the group of patients with the highest CXCL10 expression responded, especially poorly (p = 0.01). CXCL10 is a potential marker for response to radiotherapy and overall survival in patients with squamous cell carcinoma of the tongue

Genetic inhibition of neurotransmission reveals role of glutamatergic input to dopamine neurons in high-effort behavior

Midbrain dopamine neurons are crucial for many behavioral and cognitive functions. As the major excitatory input, glutamatergic afferents are important for control of the activity and plasticity of dopamine neurons. However, the role of glutamatergic input as a whole onto dopamine neurons remains unclear. Here we developed a mouse line in which glutamatergic inputs onto dopamine neurons are specifically impaired, and utilized this genetic model to directly test the role of glutamatergic inputs in dopamine-related functions. We found that while motor coordination and reward learning were largely unchanged, these animals showed prominent deficits in effort-related behavioral tasks. These results provide genetic evidence that glutamatergic transmission onto dopaminergic neurons underlies incentive motivation, a willingness to exert high levels of effort to obtain reinforcers, and have important implications for understanding the normal function of the midbrain dopamine system.Fil: Hutchison, M. A.. National Institutes of Health; Estados UnidosFil: Gu, X.. National Institutes of Health; Estados UnidosFil: Adrover, Martín Federico. National Institutes of Health; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; ArgentinaFil: Lee, M. R.. National Institutes of Health; Estados UnidosFil: Hnasko, T. S.. University of California at San Diego; Estados UnidosFil: Alvarez, V. A.. National Institutes of Health; Estados UnidosFil: Lu, W.. National Institutes of Health; Estados Unido

Can Monkeys Choose Optimally When Faced with Noisy Stimuli and Unequal Rewards?

We review the leaky competing accumulator model for two-alternative forced-choice decisions with cued responses, and propose extensions to account for the influence of unequal rewards. Assuming that stimulus information is integrated until the cue to respond arrives and that firing rates of stimulus-selective neurons remain well within physiological bounds, the model reduces to an Ornstein-Uhlenbeck (OU) process that yields explicit expressions for the psychometric function that describes accuracy. From these we compute strategies that optimize the rewards expected over blocks of trials administered with mixed difficulty and reward contingencies. The psychometric function is characterized by two parameters: its midpoint slope, which quantifies a subject's ability to extract signal from noise, and its shift, which measures the bias applied to account for unequal rewards. We fit these to data from two monkeys performing the moving dots task with mixed coherences and reward schedules. We find that their behaviors averaged over multiple sessions are close to optimal, with shifts erring in the direction of smaller penalties. We propose two methods for biasing the OU process to produce such shifts

Hippocampus Leads Ventral Striatum in Replay of Place-Reward Information

While the brain is asleep, the hippocampus plays first fiddle in the orchestra of memory; spatial information is reactivated in the hippocampus shortly in advance of emotional memory traces in the vental striatum

Changes of Mind in an Attractor Network of Decision-Making

Attractor networks successfully account for psychophysical and neurophysiological data in various decision-making tasks. Especially their ability to model persistent activity, a property of many neurons involved in decision-making, distinguishes them from other approaches. Stable decision attractors are, however, counterintuitive to changes of mind. Here we demonstrate that a biophysically-realistic attractor network with spiking neurons, in its itinerant transients towards the choice attractors, can replicate changes of mind observed recently during a two-alternative random-dot motion (RDM) task. Based on the assumption that the brain continues to evaluate available evidence after the initiation of a decision, the network predicts neural activity during changes of mind and accurately simulates reaction times, performance and percentage of changes dependent on difficulty. Moreover, the model suggests a low decision threshold and high incoming activity that drives the brain region involved in the decision-making process into a dynamical regime close to a bifurcation, which up to now lacked evidence for physiological relevance. Thereby, we further affirmed the general conformance of attractor networks with higher level neural processes and offer experimental predictions to distinguish nonlinear attractor from linear diffusion models