Active inference and oculomotor pursuit: the dynamic causal modelling of eye movements.

This paper introduces a new paradigm that allows one to quantify the Bayesian beliefs evidenced by subjects during oculomotor pursuit. Subjects' eye tracking responses to a partially occluded sinusoidal target were recorded non-invasively and averaged. These response averages were then analysed using dynamic causal modelling (DCM). In DCM, observed responses are modelled using biologically plausible generative or forward models - usually biophysical models of neuronal activity

Computational Psychiatry: towards a mathematically informed understanding of mental illness

Computational Psychiatry aims to describe the relationship between the brain's neurobiology, its environment and mental symptoms in computational terms. In so doing, it may improve psychiatric classification and the diagnosis and treatment of mental illness. It can unite many levels of description in a mechanistic and rigorous fashion, while avoiding biological reductionism and artificial categorisation. We describe how computational models of cognition can infer the current state of the environment and weigh up future actions, and how these models provide new perspectives on two example disorders, depression and schizophrenia. Reinforcement learning describes how the brain can choose and value courses of actions according to their long-term future value. Some depressive symptoms may result from aberrant valuations, which could arise from prior beliefs about the loss of agency ('helplessness'), or from an inability to inhibit the mental exploration of aversive events. Predictive coding explains how the brain might perform Bayesian inference about the state of its environment by combining sensory data with prior beliefs, each weighted according to their certainty (or precision). Several cortical abnormalities in schizophrenia might reduce precision at higher levels of the inferential hierarchy, biasing inference towards sensory data and away from prior beliefs. We discuss whether striatal hyperdopaminergia might have an adaptive function in this context, and also how reinforcement learning and incentive salience models may shed light on the disorder. Finally, we review some of Computational Psychiatry's applications to neurological disorders, such as Parkinson's disease, and some pitfalls to avoid when applying its methods

Active inference, eye movements and oculomotor delays.

This paper considers the problem of sensorimotor delays in the optimal control of (smooth) eye movements under uncertainty. Specifically, we consider delays in the visuo-oculomotor loop and their implications for active inference. Active inference uses a generalisation of Kalman filtering to provide Bayes optimal estimates of hidden states and action in generalised coordinates of motion. Representing hidden states in generalised coordinates provides a simple way of compensating for both sensory and oculomotor delays. The efficacy of this scheme is illustrated using neuronal simulations of pursuit initiation responses, with and without compensation. We then consider an extension of the generative model to simulate smooth pursuit eye movements-in which the visuo-oculomotor system believes both the target and its centre of gaze are attracted to a (hidden) point moving in the visual field. Finally, the generative model is equipped with a hierarchical structure, so that it can recognise and remember unseen (occluded) trajectories and emit anticipatory responses. These simulations speak to a straightforward and neurobiologically plausible solution to the generic problem of integrating information from different sources with different temporal delays and the particular difficulties encountered when a system-like the oculomotor system-tries to control its environment with delayed signals

Evolution of planetary systems with time-dependent stellar mass-loss

Observations indicate that intermediate mass stars, binary stars, and stellar remnants often host planets; a full explanation of these systems requires an understanding of how planetary orbits evolve as their central stars lose mass. Motivated by these dynamical systems, this paper generalizes previous studies of orbital evolution in planetary systems with stellar mass loss, with a focus on two issues: [1] Whereas most previous treatments consider constant mass loss rates, we consider single planet systems where the stellar mass loss rate is time dependent; the mass loss rate can be increasing or decreasing, but the stellar mass is always monotonically decreasing. We show that the qualitative behavior found previously for constant mass loss rates often occurs for this generalized case, and we find general conditions required for the planets to become unbound. However, for some mass loss functions, where the mass loss time scale increases faster than the orbital period, planets become unbound only in the asymptotic limit where the stellar mass vanishes. [2] We consider the chaotic evolution for two planet systems with stellar mass loss. Here we focus on a simple model consisting of analogs of Jupiter, Saturn, and the Sun. By monitoring the divergence of initially similar trajectories through time, we calculate the Lyapunov exponents of the system. This analog solar system is chaotic in the absence of mass loss with Lyapunov time τ0 ≈ 5 Myr; we find that the Lyapunov time decreases with increasing stellar mass loss rate, with a nearly linear relationship between the two time scales. Taken together, results [1] and [2] help provide an explanation for a wide range of dynamical evolution that occurs in solar systems with stellar mass loss. Subject headings: planets and satellites: dynamical evolution and stability — planet-star interactions — stars: evolution — stars: mass loss — white dwarfs – 2 – 1

Mass Drug Administration and beyond: how can we strengthen health systems to deliver complex interventions to eliminate neglected tropical diseases?

Achieving the 2020 goals for Neglected Tropical Diseases (NTDs) requires scale-up of Mass Drug Administration (MDA) which will require long-term commitment of national and global financing partners, strengthening national capacity and, at the community level, systems to monitor and evaluate activities and impact. For some settings and diseases, MDA is not appropriate and alternative interventions are required. Operational research is necessary to identify how existing MDA networks can deliver this more complex range of interventions equitably. The final stages of the different global programmes to eliminate NTDs require eliminating foci of transmission which are likely to persist in complex and remote rural settings. Operational research is required to identify how current tools and practices might be adapted to locate and eliminate these hard-to-reach foci. Chronic disabilities caused by NTDs will persist after transmission of pathogens ceases. Development and delivery of sustainable services to reduce the NTD-related disability is an urgent public health priority. LSTM and its partners are world leaders in developing and delivering interventions to control vector-borne NTDs and malaria, particularly in hard-to-reach settings in Africa. Our experience, partnerships and research capacity allows us to serve as a hub for developing, supporting, monitoring and evaluating global programmes to eliminate NTDs

Searching for an anchor in an unpredictable world: A computational model of obsessive compulsive disorder

In this article, we develop a computational model of obsessive–compulsive disorder (OCD). We propose that OCD is characterized by a difficulty in relying on past events to predict the consequences of patients’ own actions and the unfolding of possible events. Clinically, this corresponds both to patients’ difficulty in trusting their own actions (and therefore repeating them), and to their common preoccupation with unlikely chains of events. Critically, we develop this idea on the basis of the well-developed framework of the Bayesian brain, where this impairment is formalized as excessive uncertainty regarding state transitions. We illustrate the validity of this idea using quantitative simulations and use these to form specific empirical predictions. These predictions are evaluated in relation to existing evidence, and are used to delineate directions for future research. We show how seemingly unrelated findings and phenomena in OCD can be explained by the model, including a persistent experience that actions were not adequately performed and a tendency to repeat actions; excessive information gathering (i.e., checking); indecisiveness and pathological doubt; overreliance on habits at the expense of goal-directed behavior; and overresponsiveness to sensory stimuli, thoughts, and feedback. We discuss the relationship and interaction between our model and other prominent models of OCD, including models focusing on harm-avoidance, not-just-right experiences, or impairments in goal-directed behavior. Finally, we outline potential clinical implications and suggest lines for future research

Functional analysis of altered Tenascin isoform expression in breast cancer

Background: Cellular interactions with the extracellular matrix (ECM) control many aspects of cell function. The complex ECM protein Tenascin-C (TN), which exists as multiple isoforms, is upregulated in breast cancer. We previously have identified a change in the TN isoform profile in breast cancer, with detection of two additional isoforms — TN16 and TN14/16 — not seen in normal breast [1]. The purpose of this study was to investigate directly the effects of these tumour-associated TNC isoforms on breast cancer cell behaviour

The politics of negotiation and implementation: A reciprocal water access agreement in the Himalayan foothills, India

In this paper, we examine the on-the-ground realities of upstream-downstream negotiations and transactions over ecosystem services. We explore the engagement, negotiation, implementation, and postimplementation phases of a “reciprocal water access” (RWA) agreement between village communities and municipal water users at Palampur, Himachal Pradesh, India. We aim to highlight how external actors drove the payments for ecosystem services agenda through a series of facilitation and research engagements, which were pivotal to the RWA’s adoption, and how the agreement fared once external agents withdrew. In the postimplementation period, the RWA agreement continues to be upheld by upstream communities amidst evolving, competing land-use changes and claims. The introduction of cash payments for environmental services for forest-water relationships has given rise to multifaceted difficulties for the upstream hamlets, which has impeded the functionality of their forest management committee. Upstream communities’ formal rights and abilities to control and manage their resources are dynamic and need strengthening and assurance; these developments result in fluctuating transaction and opportunity costs not originally envisaged by the RWA agreement. The paper demonstrates the importance of an explicit understanding of the local politics of negotiation and implementation to determine the effectiveness of compensation-based mechanisms for the supply of ecosystem services.Natural Environment Research CouncilThis is the final version of the article. It first appeared from Resilience Alliance via http://dx.doi.org/10.5751/ES-08462-21023