Modeling habits as self-sustaining patterns of sensorimotor behavior

In the recent history of psychology and cognitive neuroscience, the notion of habit has been reduced to a stimulus-triggered response probability correlation. In this paper we use a computational model to present an alternative theoretical view (with some philosophical implications), where habits are seen as self-maintaining patterns of behavior that share properties in common with self-maintaining biological processes, and that inhabit a complex ecological context, including the presence and influence of other habits. Far from mechanical automatisms, this organismic and self-organizing concept of habit can overcome the dominating atomistic and statistical conceptions, and the high temporal resolution effects of situatedness, embodiment and sensorimotor loops emerge as playing a more central, subtle and complex role in the organization of behavior. The model is based on a novel "iterant deformable sensorimotor medium (IDSM)," designed such that trajectories taken through sensorimotor-space increase the likelihood that in the future, similar trajectories will be taken. We couple the IDSM to sensors and motors of a simulated robot, and show that under certain conditions, the IDSM conditions, the IDSM forms self-maintaining patterns of activity that operate across the IDSM, the robot's body, and the environment. We present various environments and the resulting habits that form in them. The model acts as an abstraction of habits at a much needed sensorimotor "meso-scale" between microscopic neuron-based models and macroscopic descriptions of behavior. Finally, we discuss how this model and extensions of it can help us understand aspects of behavioral self-organization, historicity and autonomy that remain out of the scope of contemporary representationalist frameworks.

Spatial-temporal excess mortality patterns of the 1918-1919 influenza pandemic in Spain

Background: The impact of socio-demographic factors and baseline health on the mortality burden of seasonal and pandemic influenza remains debated. Here we analyzed the spatial-temporal mortality patterns of the 1918 influenza pandemic in Spain, one of the countries of Europe that experienced the highest mortality burden. Methods: We analyzed monthly death rates from respiratory diseases and all-causes across 49 provinces of Spain, including the Canary and Balearic Islands, during the period January-1915 to June-1919. We estimated the influenza-related excess death rates and risk of death relative to baseline mortality by pandemic wave and province. We then explored the association between pandemic excess mortality rates and health and socio-demographic factors, which included population size and age structure, population density, infant mortality rates, baseline death rates, and urbanization. Results: Our analysis revealed high geographic heterogeneity in pandemic mortality impact. We identified 3 pandemic waves of varying timing and intensity covering the period from Jan-1918 to Jun-1919, with the highest pandemic-related excess mortality rates occurring during the months of October-November 1918 across all Spanish provinces. Cumulative excess mortality rates followed a south-north gradient after controlling for demographic factors, with the North experiencing highest excess mortality rates. A model that included latitude, population density, and the proportion of children living in provinces explained about 40% of the geographic variability in cumulative excess death rates during 1918-19, but different factors explained mortality variation in each wave. Conclusions: A substantial fraction of the variability in excess mortality rates across Spanish provinces remained unexplained, which suggests that other unidentified factors such as comorbidities, climate and background immunity may have affected the 1918-19 pandemic mortality rates. Further archeo-epidemiological research should concentrate on identifying settings with combined availability of local historical mortality records and information on the prevalence of underlying risk factors, or patient-level clinical data, to further clarify the drivers of 1918 pandemic influenza mortality.

Patterns of genetic variation in the endangered European mink (Mustela lutreola L., 1761)

Background: The European mink (Mustela lutreola, L. 1761) is a critically endangered mustelid, which inhabits several main river drainages in Europe. Here, we assess the genetic variation of existing populations of this species, including new sampling sites and additional molecular markers (newly developed microsatellite loci specific to European mink) as compared to previous studies. Probabilistic analyses were used to examine genetic structure within and between existing populations, and to infer phylogeographic processes and past demography. Results: According to both mitochondrial and nuclear microsatellite markers, Northeastern (Russia, Estonia and Belarus) and Southeastern (Romania) European populations showed the highest intraspecific diversity. In contrast, Western European (France and Spain) populations were the least polymorphic, featuring a unique mitochondrial DNA haplotype. The high differentiation values detected between Eastern and Western European populations could be the result of genetic drift in the latter due to population isolation and reduction. Genetic differences among populations were further supported by Bayesian clustering and two main groups were confirmed (Eastern vs. Western Europe) along with two contained subgroups at a more local scale (Northeastern vs. Southeastern Europe; France vs. Spain). Conclusions: Genetic data and performed analyses support a historical scenario of stable European mink populations, not affected by Quaternary climate oscillations in the Late Pleistocene, and posterior expansion events following river connections in both North-and Southeastern European populations. This suggests an eastern refuge during glacial maxima (as already proposed for boreal and continental species). In contrast, Western Europe was colonised more recently following either natural expansions or putative human introductions. Low levels of genetic diversity observed within each studied population suggest recent bottleneck events and stress the urgent need for conservation measures to counteract the demographic decline experienced by the European mink.

Patterns of Impact Resulting from a 'Sit Less, Move More' Web-Based Program in Sedentary Office Employees

Purpose Encouraging office workers to 'sit less and move more' encompasses two public health priorities. However, there is little evidence on the effectiveness of workplace interventions for reducing sitting, even less about the longer term effects of such interventions and still less on dual-focused interventions. This study assessed the short and mid-term impacts of a workplace web-based intervention (Walk@WorkSpain, W@WS; 2010-11) on self-reported sitting time, step counts and physical risk factors (waist circumference, BMI, blood pressure) for chronic disease. Methods Employees at six Spanish university campuses (n=264; 42 +/- 10 years; 171 female) were randomly assigned by worksite and campus to an Intervention (used W@WS; n=129; 87 female) or a Comparison group (maintained normal behavior; n=135; 84 female). This phased, 19-week program aimed to decrease occupational sitting time through increased incidental movement and short walks. A linear mixed model assessed changes in outcome measures between the baseline, ramping (8 weeks), maintenance (11 weeks) and follow-up (two months) phases for Intervention versus Comparison groups. Results A significant 2 (group) x 2 (program phases) interaction was found for self-reported occupational sitting (F[3]=7.97, p=0.046), daily step counts (F[3]=15.68, p=0.0013) and waist circumference (F[3]=11.67, p=0.0086). The Intervention group decreased minutes of daily occupational sitting while also increasing step counts from baseline (446 +/- 126; 8,862 +/- 2,475) through ramping (+425 +/- 120; 9,345 +/- 2,435), maintenance (+422 +/- 123; 9,638 +/- 3,131) and follow-up (+414 +/- 129; 9,786 +/- 3,205). In the Comparison group, compared to baseline (404 +/- 106), sitting time remained unchanged through ramping and maintenance, but decreased at follow-up (-388 +/- 120), while step counts diminished across all phases. The Intervention group significantly reduced waist circumference by 2.1cms from baseline to follow-up while the Comparison group reduced waist circumference by 1.3cms over the same period. Conclusions W@WSis a feasible and effective evidence-based intervention that can be successfully deployed with sedentary employees to elicit sustained changes on "sitting less and moving more".

Can environmental constraints determine random patterns of plant species co-occurrence?

Plant community ecologists use the null model approach to infer assembly processes from observed patterns of species co-occurrence. In about a third of published studies, the null hypothesis of random assembly cannot be rejected. When this occurs, plant ecologists interpret that the observed random pattern is not environmentally constrained - but probably generated by stochastic processes. The null model approach (using the C-score and the discrepancy index) was used to test for random assembly under two simulation algorithms. Logistic regression, distance-based redundancy analysis, and constrained ordination were used to test for environmental determinism (species segregation along environmental gradients or turnover and species aggregation). This article introduces an environmentally determined community of alpine hydrophytes that presents itself as randomly assembled. The pathway through which the random pattern arises in this community is suggested to be as follows: Two simultaneous environmental processes, one leading to species aggregation and the other leading to species segregation, concurrently generate the observed pattern, which results to be neither aggregated nor segregated - but random. A simulation study supports this suggestion. Although apparently simple, the null model approach seems to assume that a single ecological factor prevails or that if several factors decisively influence the community, then they all exert their influence in the same direction, generating either aggregation or segregation. As these assumptions are unlikely to hold in most cases and assembly processes cannot be inferred from random patterns, we would like to propose plant ecologists to investigate specifically the ecological processes responsible for observed random patterns, instead of trying to infer processes from patterns