Neural Correlates of Intentional Communication

We know a great deal about the neurophysiological mechanisms supporting instrumental actions, i.e., actions designed to alter the physical state of the environment. In contrast, little is known about our ability to select communicative actions, i.e., actions directly designed to modify the mental state of another agent. We have recently provided novel empirical evidence for a mechanism in which a communicator selects his actions on the basis of a prediction of the communicative intentions that an addressee is most likely to attribute to those actions. The main novelty of those findings was that this prediction of intention recognition is cerebrally implemented within the intention recognition system of the communicator, is modulated by the ambiguity in meaning of the communicative acts, and not by their sensorimotor complexity. The characteristics of this predictive mechanism support the notion that human communicative abilities are distinct from both sensorimotor and linguistic processes

Modulation of Litter Decomposition by the Soil Microbial Food Web Under Influence of Land Use Change

Soil microbial communities modulate soil organic matter (SOM) dynamics by catalyzing litter decomposition. However, our understanding of how litter-derived carbon (C) flows through the microbial portion of the soil food web is far from comprehensive. This information is necessary to facilitate reliable predictions of soil C cycling and sequestration in response to a changing environment such as land use change in the form of agricultural abandonment. To examine the flow of litter-derived C through the soil microbial food web and it’s response to land use change, we carried out an incubation experiment with soils from six fields; three recently abandoned and three long term abandoned fields. In these soils, the fate of 13C-labeled plant litter was followed by analyzing phospholipid fatty acids (PLFA) over a period of 56 days. The litter-amended soils were sampled over time to measure 13CO2 and mineral N dynamics. Microbial 13C-incorporation patterns revealed a clear succession of microbial groups during litter decomposition. Fungi were first to incorporate 13C-label, followed by G− bacteria, G+ bacteria, actinomycetes and micro-fauna. The order in which various microbial groups responded to litter decomposition was similar across all the fields examined, with no clear distinction between recent and long-term abandoned soils. Although the microbial biomass was initially higher in long-term abandoned soils, the net amount of 13C-labeled litter that was incorporated by the soil microbial community was ultimately comparable between recent and long-term abandoned fields. In relative terms, this means there was a higher efficiency of litter-derived 13C-incorporation in recent abandoned soil microbial communities compared to long-term abandoned soils, most likely due to a net shift from SOM-derived C toward root-derived C input in the soil microbial food web following land-abandonment

Brain Mechanisms Underlying Human Communication

Human communication has been described as involving the coding-decoding of a conventional symbol system, which could be supported by parts of the human motor system (i.e. the “mirror neurons system”). However, this view does not explain how these conventions could develop in the first place. Here we target the neglected but crucial issue of how people organize their non-verbal behavior to communicate a given intention without pre-established conventions. We have measured behavioral and brain responses in pairs of subjects during communicative exchanges occurring in a real, interactive, on-line social context. In two fMRI studies, we found robust evidence that planning new communicative actions (by a sender) and recognizing the communicative intention of the same actions (by a receiver) relied on spatially overlapping portions of their brains (the right posterior superior temporal sulcus). The response of this region was lateralized to the right hemisphere, modulated by the ambiguity in meaning of the communicative acts, but not by their sensorimotor complexity. These results indicate that the sender of a communicative signal uses his own intention recognition system to make a prediction of the intention recognition performed by the receiver. This finding supports the notion that our communicative abilities are distinct from both sensorimotor processes and language abilities

The influence of entrance constriction on hydrodynamics and intertidal morphology within estuarine basins

We investigate the influence of basin entrance constriction on current velocities, tidal asymmetry, bed shear stresses and intertidal morphology by using a numerical model developed in Delft3D. Hypsometric curves created for six sub-estuaries within Tauranga Harbour indicate a possible link between intertidal hypsometry and entrance constriction. Model results for both spring- and neap tidal cycles show that a constricted subestuary with a deep entrance channel is associated with low current velocities and bed shear stresses in the centre of the basin– conditions favourable for sediment deposition. These constricted geometries are shown to be characterized by convex intertidal equilibrium profiles. Unconstricted sub-estuary model results display an even distribution of relatively high current velocities and bed shear stresses resulting in potential for erosion throughout the estuary. The unconstricted basins in our study are mainly associated with concave intertidal equilibrium profiles. Flood dominance increases from the entrance further into the estuary for both constricted and unconstricted conditions

The effectiveness of attentional bias modification for substance use disorder symptoms in adults:a systematic review

Background: Attentional bias modification (ABM) interventions have been developed to address addiction by reducing attentional bias for substance-related cues. This study provides a systematic review of the effectiveness of ABM interventions in decreasing symptoms of addictive behaviour, taking baseline levels of attentional bias and changes in attentional bias into account. Methods: We included randomised and non-randomised studies that investigated the effectiveness of ABM interventions in heavy-using adults and treatment-seeking individuals with symptoms of substance use disorder to manipulate attentional bias and to reduce substance use-related symptoms. We searched for relevant English peer-reviewed articles without any restriction for the year of publication using PsycINFO, PubMed, and ISI Web in August 2016. Study quality was assessed regarding reporting, external validity, internal validity, and power of the study. Results: Eighteen studies were included: nine studies reported on ABM intervention effects in alcohol use, six studies on nicotine use, and three studies on opiate use. The included studies differed with regard to type of ABM intervention (modified dot probe task n = 14; Alcohol Attention Control Training Programme n = 4), outcome measures, amount and length of provided sessions, and context (clinic versus laboratory versus home environment). The study quality mostly ranged from low average to high average (one study scored below the quality cut-off). Ten studies reported significant changes of symptoms of addictive behaviour, whereas eight studies found no effect of ABM interventions on symptoms. However, when restricted to multi-session ABM intervention studies, eight out of ten studies found effects on symptoms of addiction. Surprisingly, these effects on symptoms of addictive behaviour showed no straightforward relationship with baseline attentional bias and its change from baseline to post-test. Conclusions: Despite a number of negative findings and the diversity of studies, multi-session ABM interventions, especially in the case of alcohol and when the Alcohol Attention Control Training Programme was used, appear to have positive effects on symptoms of addictive behaviour. However, more rigorous well-powered future research in clinical samples is needed before firm conclusions regarding the effectiveness of ABM interventions can be drawn

23 High Redshift Supernovae from the IfA Deep Survey: Doubling the SN Sample at z>0.7

We present photometric and spectroscopic observations of 23 high redshift supernovae spanning a range of z=0.34-1.03, 9 of which are unambiguously classified as Type Ia. These supernovae were discovered during the IfA Deep Survey, which began in September 2001 and observed a total of 2.5 square degrees to a depth of approximately m=25-26 in RIZ over 9-17 visits, typically every 1-3 weeks for nearly 5 months, with additional observations continuing until April 2002. We give a brief description of the survey motivations, observational strategy, and reduction process. This sample of 23 high-redshift supernovae includes 15 at z>0.7, doubling the published number of objects at these redshifts, and indicates that the evidence for acceleration of the universe is not due to a systematic effect proportional to redshift. In combination with the recent compilation of Tonry et al. (2003), we calculate cosmological parameter density contours which are consistent with the flat universe indicated by the CMB (Spergel et al. 2003). Adopting the constraint that Omega_total = 1.0, we obtain best-fit values of (Omega_m, Omega_Lambda)=(0.33, 0.67) using 22 SNe from this survey augmented by the literature compilation. We show that using the empty-beam model for gravitational lensing does not eliminate the need for Omega_Lambda > 0. Experience from this survey indicates great potential for similar large-scale surveys while also revealing the limitations of performing surveys for z>1 SNe from the ground.Comment: 67 pages, 12 figures, 12 tables, accepted for publication in the Astrophysical Journa

How habitat-modifying organisms structure the food web of two coastal ecosystems

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Stability and Fluctuations in Complex Ecological Systems

From 08-12 August, 2022, 32 individuals participated in a workshop, Stability and Fluctuations in Complex Ecological Systems, at the Lorentz Center, located in Leiden, The Netherlands. An interdisciplinary dialogue between ecologists, mathematicians, and physicists provided a foundation of important problems to consider over the next 5-10 years. This paper outlines eight areas including (1) improving our understanding of the effect of scale, both temporal and spatial, for both deterministic and stochastic problems; (2) clarifying the different terminologies and definitions used in different scientific fields; (3) developing a comprehensive set of data analysis techniques arising from different fields but which can be used together to improve our understanding of existing data sets; (4) having theoreticians/computational scientists collaborate closely with empirical ecologists to determine what new data should be collected; (5) improving our knowledge of how to protect and/or restore ecosystems; (6) incorporating socio-economic effects into models of ecosystems; (7) improving our understanding of the role of deterministic and stochastic fluctuations; (8) studying the current state of biodiversity at the functional level, taxa level and genome level.Comment: 22 page