Simple individual-based models effectively represent Afrotropical forest bird movement in complex landscapes

Reliable estimates of dispersal rates between habitat patches (i.e. functional connectivity) are critical for predicting long-term effects of habitat fragmentation on population persistence. Connectivity measures are frequently derived from least cost path or graph-based approaches, despite the fact that these methods make biologically unrealistic assumptions. Individual-based models (IBMs) have been proposed as an alternative as they allow modelling movement behaviour in response to landscape resistance. However, IBMs typically require excessive data to be useful for management. Here, we test the extent to which an IBM requiring only an uncomplicated set of movement rules [the 'stochastic movement simulator' (SMS)] can predict animal movement behaviour in real-world landscapes. Movement behaviour of two forest birds, the Cabanis's greenbul Phyllastrephus cabanisi (a forest specialist) and the white-starred robin Pogonocichla stellata (a habitat generalist), across an Afrotropical matrix was simulated using SMS. Predictions from SMS were evaluated against a set of detailed movement paths collected by radiotracking homing individuals. SMS was capable of generating credible predictions of bird movement, although simulations were sensitive to the cost values and the movement rules specified. Model performance was generally highest when movement was simulated across low-contrasting cost surfaces and when virtual individuals were assigned low directional persistence and limited perceptual range. SMS better predicted movements of the habitat specialist than the habitat generalist, which highlights its potential to model functional connectivity when species movements are affected by the matrix. Synthesis and applications. Modelling the dispersal process with greater biological realism is likely to be critical for improving our predictive capability regarding functional connectivity and population persistence. For more realistic models to be widely applied, it is vital that their application is not overly complicated or data demanding. Here, we show that given relatively basic understanding of a species' dispersal ecology, the stochastic movement simulator represents a promising tool for estimating connectivity, which can help improve the design of functional ecological networks aimed at successful species conservation

Multiple multidimensional morse wavelets

This paper defines a set of operators that localize a radial image in space and radial frequency simultaneously. The eigenfunctions of the operator are determined and a nonseparable orthogonal set of radial wavelet functions are found. The eigenfunctions are optimally concentrated over a given region of radial space and scale space, defined via a triplet of parameters. Analytic forms for the energy concentration of the functions over the region are given. The radial function localization operator can be generalised to an operator localizing any L-2(R-2) function. It is demonstrated that the latter operator, given an appropriate choice of localization region, approximately has the same radial eigenfunctions as the radial operator. Based on a given radial wavelet function a quaternionic wavelet is defined that can extract the local orientation of discontinuous signals as well as amplitude, orientation and phase structure of locally oscillatory signals. The full set of quaternionic wavelet functions are component by component orthogonal; their statistical properties are tractable, and forms for the variability of the estimators of the local phase and orientation are given, as well as the local energy of the image. By averaging estimators across wavelets, a substantial reduction in the variance is achieved

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

A Model of Movement Coordinates in Motor Cortex: Posture-Dependent Changes in the Gain and Direction of Single Cell Tuning Curves

Central to the problem of elucidating the cortical mechanisms that mediate movement behavior is an investigation of the coordinate systems by which movement variables are encoded in the firing rates of individual motor cortical neurons. In the last decade, neurophysiologists have probed how the preferred direction of an individual motor cortical cell (as determined by a center-out task) will change with posture because such changes are useful for inferring underlying cordinates. However, while the importance of shifts in preferred direction is well-known and widely accepted, posture-dependent changes in the depth of modulation of a cell's tuning curve, i.e. gain changes, have not been similarly identified as a means of coordinate inference. This paper develops a vector field framework which, by viewing the preferred direction and the gain of a cell's tuning curve as dual components of a unitary response vector, can compute how each aspect of cell response covaries with posture as a function of the coordinate system in which a given cell is hypothesized to encode its movement information. This integrated approach leads to a model of motor cortical cell activity that codifies the following four observations: 1) cell activity correlates with hand movement direction, 2) cell activity correlates with hand movement speed, 3) preferred directions vary with posture, and 4) the modulation depth of tuning curves varies with posture. Finally, the model suggests general methods for testing coordinate hypotheses at the single cell level and example protocols arc simulated for three possible coordinate systems: Cartesian spatial, shoulder-centered, and joint angle.Defense Advanced Research Projects Agency (N00014-92-J-4015); Defense Advanced Research Projects Agency and the Office of Naval Research (N00014-95-1-0409); National Science Foundation (IRI-90-00530, IRI-97-20333); Office of Naval Research (N00014-91-J-4100, N00014-92-J-1309, N00014-94-l-0940, N00014-95-1-0657)

The connection between action and perception

This thesis consists of three main studies that cover complementary aspects of action-to-perception transfer. In the recent decades, cognitive psychology has started a paradigm shift from its traditional approach to put the stimulus first and treat the action as response to a less one-directional view of perception and action. Quite trivially, action influences perception by changing the external world: we move objects, we locomote or we move our sensory organs. More crucially, action also influences perception internally. Study II and III will address this question directly, by studying perceptual effects of action on physically unchanged stimuli. Study I deals with biological motion. I will argue that the perception of biological motion may present a naturalistic example for direct action-to-perception transfer. The cues of animate locomotion are detected rapidly and effortlessly, and allow quick retrieval of detailed information about the actor, as we related to our immense experience with moving our own bodies in ways that correspond to the physical “laws” which the dynamics of these cues represent. In sum, the studies reported in this thesis provide novel insight on shared action-perception representations, their perceptual consequences and their relation to cognitive models of the world. In Study I, we showed that biological motion cues distort the perceived size of the actor’s figure: a biological motion stimulus is perceived larger than matched control stimuli and lets subsequent stimuli appear smaller. Provided the importance of biological motion, this is in line with other studies that relate subjective importance to perceived size – however, the connection with animate motion has not been reported earlier. If there are shared action-perception representations, do they operate on different representational levels? In Study II, we coupled a stimulus that was in competition with another to action more or less strongly. While the degree of action-perception coupling did not affect overt reports of stimulus’ visibility, oculomotor measures were modulated. This suggests different degrees of action perception coupling on different representational levels, with varying access to awareness. Does in turn the internal cognitive model of the world penetrate action perception coupling? In Study III, we showed that the effect of action-perception congruency on perceptual stability critically depends on the internal cognitive model of action perception coupling. Studies II and III together indicate that no single mechanism or representation can account for all action-perception findings. In the general discussion, I will consider the needed adjustments to current models as well as alternative theoretical approaches

Combining Context and Knowledge Representations for Chemical-Disease Relation Extraction

Automatically extracting the relationships between chemicals and diseases is significantly important to various areas of biomedical research and health care. Biomedical experts have built many large-scale knowledge bases (KBs) to advance the development of biomedical research. KBs contain huge amounts of structured information about entities and relationships, therefore plays a pivotal role in chemical-disease relation (CDR) extraction. However, previous researches pay less attention to the prior knowledge existing in KBs. This paper proposes a neural network-based attention model (NAM) for CDR extraction, which makes full use of context information in documents and prior knowledge in KBs. For a pair of entities in a document, an attention mechanism is employed to select important context words with respect to the relation representations learned from KBs. Experiments on the BioCreative V CDR dataset show that combining context and knowledge representations through the attention mechanism, could significantly improve the CDR extraction performance while achieve comparable results with state-of-the-art systems.Comment: Published on IEEE/ACM Transactions on Computational Biology and Bioinformatics, 11 pages, 5 figure

Functional connectivity and neuronal dynamics: insights from computational methods

International audienceBrain functions rely on flexible communication between microcircuits in distinct cortical regions. The mechanisms underlying flexible information routing are still, however, largely unknown. Here, we hypothesize that the emergence of a multiplicity of possible information routing patterns is due to the richness of the complex dynamics that can be supported by an underlying structural network. Analyses of circuit computational models of interacting brain areas suggest that different dynamical states associated with a given connectome mechanistically implement different information routing patterns between system's components. As a result, a fast, network-wide and self-organized reconfiguration of information routing patterns-and Functional Connectivity networks, seen as their proxy-can be achieved by inducing a transition between the available intrinsic dynamical states. We present here a survey of theoretical and modelling results, as well as of sophisticated metrics of Functional Connectivity which are compliant with the daunting task of characterizing dynamic routing from neural data. Theory: Function follows dynamics, rather than structure Neuronal activity conveys information, but which target should this information be-pushed‖ to, or which source should new information be-pulled‖ from? The problem of dynamic information routing is ubiquitous in a distributed information processing system as the brain. Brain functions in general require the control of distributed networks of interregional communication on fast timescales compliant with behavior, but incompatible with plastic modifications of connectivity tracts (Bressler & Kelso, 2001; Varela et al., 2001). This argument led to notions of connectivity based on information exchange-or more generically, an-interaction‖-between brain regions or neuronal populations, rather than based on the underlying STRUCTURAL CONNECTIVITY (SC, i.e. anatomic). An entire zoo of data-driven metrics has been introduced in the literature and this chapter will review some of them. Notwithstanding, they track simple correlation, or directed causal influence (Friston, 2011) or information transfer (Wibral et al., 2014) between time-series of activity. Thes

The Control of Amplitude and Direction in Bimanual Coordination

Spatial coordination of bimanual movements is important when performing daily activities. Whereas, older adults and individuals with Parkinson’s disease (PD) commonly show difficulties in temporally coordinating the hands in bimanual coordination tasks, the effects of aging and Parkinson’s disease on the quality of spatial coordination between the hands are unclear. Thus, the present work investigated the impact of older age and PD on the spatial interference in a bimanual task in which 48 right hand-dominant participants (16 young adults, 16 older adults and 16 individuals with PD) drew simultaneously two lines with both hands with varied movement amplitudes (3 and 6 cm) and/or directions (horizontal and vertical). The dependent variables were amplitude error of the line drawn with the right hand (A-error-R), amplitude error of the line drawn with the left hand (A-error-L), directional error of the line drawn with the right hand (D-error-R) and directional error of the line drawn with the left hand (D-error-L). The results showed that older adults were able to maintain a similar level of spatial accuracy on the dominant side as young adults, but they showed reduced spatial accuracy when using the non-dominant hand. Furthermore, advanced age altered the control of movement direction in the bimanual coordination task, but not the control of movement amplitude. These results indicate that, the effects of the use of a longer standard spatial code for movement amplitude did not change in older adults, but older age does alter the control of direction in bimanual movements. Individuals with Parkinson’s disease and older adults showed similar levels of spatial accuracy, except for the directional accuracy of the lines drawn with the dominant hand; these lines showed angles with the target direction were increased about two degree in the PD group as compared to older control group. In summary, the quality of spatial coordination declined only in part in older adults, and the decline in the quality of spatial coordination was not exacerbated in individuals with PD, indicating the divergent role of basal ganglia for the control of temporal and spatial aspects