Search

The aim of this study was to create a novel metric, Expected Pass Turnovers (xPT), that could evaluate possession retention from player-passing events in football. Event and positional data were analysed from all 380 matches in the 2020/21 English Premier League season, which encompassed 256,433 passes in the final dataset. A logistic mixed-effects model was implemented to attribute the probability of each pass getting turned over. The use of positional data enabled the identification of a) opposition players present in radii surrounding the ball carrier and b) availability of teammates with respect to the ball carrier. The addition of these positional features improved the accuracy (+6.1 AUC Score) of the model. xPT serves as a practitioner Key Performance Indicator, as analysts can identify players that lose possession more often or not than expected, given the situational context of each pass, from game to game. Future work may include modelling the turnover probability of dribble and carry actions, as this would lead to a more comprehensive understanding of turnover events in football.

Human cognition is not always tethered to events in the external world. Laboratory and real world experience sampling studies reveal that attention is often devoted to self-generated mental content rather than to events taking place in the immediate environment. Recent studies have begun to explicitly examine the consistency between states of off-task thought in the laboratory and in daily life, highlighting differences in the psychological correlates of these states across the two contexts. Our study used neuroimaging to further understand the generalizability of off-task thought across laboratory and daily life contexts. We examined (1) whether context (daily life versus laboratory) impacts on individuals' off-task thought patterns and whether individual variations in these patterns are correlated across contexts; (2) whether neural correlates for the patterns of off-task thoughts in the laboratory show similarities with those thoughts in daily life, in particular, whether differences in cortical grey matter associated with detail and off-task thoughts in the para-hippocampus, identified in a prior study on laboratory thoughts, were apparent in real life thought patterns. We also measured neural responses to common real-world stimuli (faces and scenes) and examined how neural responses to these stimuli were related to experiences in the laboratory and in daily life - finding evidence of both similarities and differences. There were consistent patterns of off-task thoughts reported across the two contexts, and both patterns had a commensurate relationship with medial temporal lobe architecture. However, compared to real world off-task thoughts, those in the laboratory focused more on social content and showed a stronger correlation with neural activity when viewing faces compared to scenes. Overall our results show that off-task thought patterns have broad similarities in the laboratory and in daily life, and the apparent differences may be, in part, driven by the richer environmental context in the real world. More generally, our findings are broadly consistent with emerging evidence that shows off-task thoughts emerge through the prioritisation of information that has greater personal relevance than events in the here and now., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Neural activity within the default mode network (DMN) is widely assumed to relate to processing during off-task states, however it remains unclear whether this association emerges from a shared role in self or social content that is common in these conditions. In the current study, we examine the possibility that the role of the DMN in ongoing thought emerges from contributions to specific features of off-task experience such as self-relevant or social content. A group of participants described their experiences while performing a laboratory task over a period of days. In a different session, neural activity was measured while participants performed Self/Other judgements (e.g., Does the word 'Honest' apply to you (Self condition) or Barack Obama (Other condition)). Despite the prominence of social and personal content in off-task reports, there was no association with neural activity during off-task trait adjective judgements. Instead, during both Self and Other judgements we found recruitment of caudal posterior cingulate cortex-a core DMN hub-was above baseline for individuals whose laboratory experiences were characterised as detailed. These data provide little support for a role of the DMN in self or other content in the off-task state and instead suggest a role in how on-going thought is represented., Competing Interests: The authors have declared that no competing interests exist.

Regions of transmodal cortex, in particular the default mode network (DMN), have historically been argued to serve functions unrelated to task performance, in part because of associations with naturally occurring periods of off-task thought. In contrast, contemporary views of the DMN suggest it plays an integrative role in cognition that emerges from its location at the top of a cortical hierarchy and its relative isolation from systems directly involved in perception and action. The combination of these topographical features may allow the DMN to support abstract representations derived from lower levels in the hierarchy and so reflect the broader cognitive landscape. To investigate these contrasting views of DMN function, we sampled experience as participants performed tasks varying in their working-memory load while inside an fMRI scanner. We used self-report data to establish dimensions of thought that describe levels of detail, the relationship to a task, the modality of thought, and its emotional qualities. We used representational similarity analysis to examine correspondences between patterns of neural activity and each dimension of thought. Our results were inconsistent with a task-negative view of DMN function. Distinctions between on- and off-task thought were associated with patterns of consistent neural activity in regions adjacent to unimodal cortex, including motor and premotor cortex. Detail in ongoing thought was associated with patterns of activity within the DMN during periods of working-memory maintenance. These results demonstrate a contribution of the DMN to ongoing cognition extending beyond task-unrelated processing that can include detailed experiences occurring under active task conditions., Competing Interests: The authors declare no conflict of interest., (Copyright © 2018 the Author(s). Published by PNAS.)

The default mode network supports a variety of mental operations such as semantic processing, episodic memory retrieval, mental time travel and mind-wandering, yet the commonalities between these functions remains unclear. One possibility is that this system supports cognition that is independent of the immediate environment; alternatively or additionally, it might support higher-order conceptual representations that draw together multiple features. We tested these accounts using a novel paradigm that separately manipulated the availability of perceptual information to guide decision-making and the representational complexity of this information. Using task based imaging we established regions that respond when cognition combines both stimulus independence with multi-modal information. These included left and right angular gyri and the left middle temporal gyrus. Although these sites were within the default mode network, they showed a stronger response to demanding memory judgements than to an easier perceptual task, contrary to the view that they support automatic aspects of cognition. In a subsequent analysis, we showed that these regions were located at the extreme end of a macroscale gradient, which describes gradual transitions from sensorimotor to transmodal cortex. This shift in the focus of neural activity towards transmodal, default mode, regions might reflect a process of where the functional distance from specific sensory enables conceptually rich and detailed cognitive states to be generated in the absence of input., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)

It is well recognized that the default mode network (DMN) is involved in states of imagination, although the cognitive processes that this association reflects are not well understood. The DMN includes many regions that function as cortical "hubs", including the posterior cingulate/retrosplenial cortex, anterior temporal lobe and the hippocampus. This suggests that the role of the DMN in cognition may reflect a process of cortical integration. In the current study we tested whether functional connectivity from uni-modal regions of cortex into the DMN is linked to features of imaginative thought. We found that strong intrinsic communication between visual and retrosplenial cortex was correlated with the degree of social thoughts about the future. Using an independent dataset, we show that the same region of retrosplenial cortex is functionally coupled to regions of primary visual cortex as well as core regions that make up the DMN. Finally, we compared the functional connectivity of the retrosplenial cortex, with a region of medial prefrontal cortex implicated in the integration of information from regions of the temporal lobe associated with future thought in a prior study. This analysis shows that the retrosplenial cortex is preferentially coupled to medial occipital, temporal lobe regions and the angular gyrus, areas linked to episodic memory, scene construction and navigation. In contrast, the medial prefrontal cortex shows preferential connectivity with motor cortex and lateral temporal and prefrontal regions implicated in language, motor processes and working memory. Together these findings suggest that integrating neural information from visual cortex into retrosplenial cortex may be important for imagining the future and may do so by creating a mental scene in which prospective simulations play out. We speculate that the role of the DMN in imagination may emerge from its capacity to bind together distributed representations from across the cortex in a coherent manner., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Contemporary theories assume that semantic cognition emerges from a neural architecture in which different component processes are combined to produce aspects of conceptual thought and behaviour. In addition to the state-level, momentary variation in brain connectivity, individuals may also differ in their propensity to generate particular configurations of such components, and these trait-level differences may relate to individual differences in semantic cognition. We tested this view by exploring how variation in intrinsic brain functional connectivity between semantic nodes in fMRI was related to performance on a battery of semantic tasks in 154 healthy participants. Through simultaneous decomposition of brain functional connectivity and semantic task performance, we identified distinct components of semantic cognition at rest. In a subsequent validation step, these data-driven components demonstrated explanatory power for neural responses in an fMRI-based semantic localiser task and variation in self-generated thoughts during the resting-state scan. Our findings showed that good performance on harder semantic tasks was associated with relative segregation at rest between frontal brain regions implicated in controlled semantic retrieval and the default mode network. Poor performance on easier tasks was linked to greater coupling between the same frontal regions and the anterior temporal lobe; a pattern associated with deliberate, verbal thematic thoughts at rest. We also identified components that related to qualities of semantic cognition: relatively good performance on pictorial semantic tasks was associated with greater separation of angular gyrus from frontal control sites and greater integration with posterior cingulate and anterior temporal cortex. In contrast, good speech production was linked to the separation of angular gyrus, posterior cingulate and temporal lobe regions. Together these data show that quantitative and qualitative variation in semantic cognition across individuals emerges from variations in the interaction of nodes within distinct functional brain networks., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Experiences such as mind-wandering illustrate that cognition is not always tethered to events in the here-and-now. Although converging evidence emphasises the default mode network (DMN) in mind-wandering, its precise contribution remains unclear. The DMN comprises cortical regions that are maximally distant from primary sensory and motor cortex, a topological location that may support the stimulus-independence of mind-wandering. The DMN is functionally heterogeneous, comprising regions engaged by memory, social cognition and planning; processes relevant to mind-wandering content. Our study examined the relationships between: (i) individual differences in resting-state DMN connectivity, (ii) performance on memory, social and planning tasks and (iii) variability in spontaneous thought, to investigate whether the DMN is critical to mind-wandering because it supports stimulus-independent cognition, memory retrieval, or both. Individual variation in task performance modulated the functional organization of the DMN: poor external engagement was linked to stronger coupling between medial and dorsal subsystems, while decoupling of the core from the cerebellum predicted reports of detailed memory retrieval. Both patterns predicted off-task future thoughts. Consistent with predictions from component process accounts of mind-wandering, our study suggests a 2-fold involvement of the DMN: (i) it supports experiences that are unrelated to the environment through strong coupling between its sub-systems; (ii) it allows memory representations to form the basis of conscious experience., (© The Author (2017). Published by Oxford University Press.)

The hippocampus contributes to episodic, spatial and semantic aspects of memory, yet individual differences within and between these functions are not well-understood. In 136 healthy individuals, we investigated whether these differences reflect variation in the strength of connections between functionally-specialised segments of the hippocampus and diverse cortical regions that participate in different aspects of memory. Better topographical memory was associated with stronger connectivity between lingual gyrus and left anterior, rather than posterior, hippocampus. Better semantic memory was associated with increased connectivity between the intracalcarine/cuneus and left, rather than right, posterior hippocampus. Notably, we observed a double dissociation between semantic and topographical memory: better semantic memory was associated with stronger connectivity between left temporoparietal cortex and left anterior hippocampus, while better topographic memory was linked to stronger connectivity with right anterior hippocampus. Together these data support a division-of-labour account of hippocampal functioning: at the population level, differences in connectivity across the hippocampus reflect functional specialisation for different facets of memory, while variation in these connectivity patterns across individuals is associated with differences in the capacity to retrieve different types of information. In particular, within-hemisphere connectivity between hippocampus and left temporoparietal cortex supports conceptual processing at the expense of spatial ability., (Copyright © 2017. Published by Elsevier Inc.)

Theoretical accounts of face processing often emphasise feature shapes as the primary visual cue to the recognition of facial expressions. However, changes in facial expression also affect the surface properties of the face. In this study, we investigated whether this surface information can also be used in the recognition of facial expression. First, participants identified facial expressions (fear, anger, disgust, sadness, happiness) from images that were manipulated such that they varied mainly in shape or mainly in surface properties. We found that the categorization of facial expression is possible in either type of image, but that different expressions are relatively dependent on surface or shape properties. Next, we investigated the relative contributions of shape and surface information to the categorization of facial expressions. This employed a complementary method that involved combining the surface properties of one expression with the shape properties from a different expression. Our results showed that the categorization of facial expressions in these hybrid images was equally dependent on the surface and shape properties of the image. Together, these findings provide a direct demonstration that both feature shape and surface information make significant contributions to the recognition of facial expressions., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

The ability to perceive facial expressions of emotion is essential for effective social communication. We investigated how the perception of facial expression emerges from the image properties that convey this important social signal, and how neural responses in face-selective brain regions might track these properties. To do this, we measured the perceptual similarity between expressions of basic emotions, and investigated how this is reflected in image measures and in the neural response of different face-selective regions. We show that the perceptual similarity of different facial expressions (fear, anger, disgust, sadness, happiness) can be predicted by both surface and feature shape information in the image. Using block design fMRI, we found that the perceptual similarity of expressions could also be predicted from the patterns of neural response in the face-selective posterior superior temporal sulcus (STS), but not in the fusiform face area (FFA). These results show that the perception of facial expression is dependent on the shape and surface properties of the image and on the activity of specific face-selective regions., (Copyright © 2016 Elsevier Inc. All rights reserved.)

The amygdala is known to play an important role in the response to facial expressions that convey fear. However, it remains unclear whether the amygdala's response to fear reflects its role in the interpretation of danger and threat, or whether it is to some extent activated by all facial expressions of emotion. Previous attempts to address this issue using neuroimaging have been confounded by differences in the use of control stimuli across studies. Here, we address this issue using a block design functional magnetic resonance imaging paradigm, in which we compared the response to face images posing expressions of fear, anger, happiness, disgust and sadness with a range of control conditions. The responses in the amygdala to different facial expressions were compared with the responses to a non-face condition (buildings), to mildly happy faces and to neutral faces. Results showed that only fear and anger elicited significantly greater responses compared with the control conditions involving faces. Overall, these findings are consistent with the role of the amygdala in processing threat, rather than in the processing of all facial expressions of emotion, and demonstrate the critical importance of the choice of comparison condition to the pattern of results., (© The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.)

Reversing the luminance values of a face (contrast negation) is known to disrupt recognition. However, the effects of contrast negation are attenuated in chimeric images, in which the eye region is returned to positive contrast (S. Gilad, M. Meng, & P. Sinha, 2009, Role of ordinal contrast relationships in face encoding, Proceedings of the National Academy of Sciences, USA, Vol. 106, pp. 5353-5358). Here, we probe further the importance of the eye region for the representation of facial identity. In the first experiment, we asked to what extent the chimeric benefit is specific to the eye region. Our results showed a benefit for including a positive eye region in a contrast negated face, whereas chimeric faces in which only the forehead, nose, or mouth regions were returned to positive contrast did not significantly improve recognition. In Experiment 2, we confirmed that the presence of positive contrast eyes alone does not account for the improved recognition of chimeric face images. Rather, it is the integration of information from the positive contrast eye region and the surrounding negative contrast face that is essential for the chimeric benefit. In Experiment 3, we demonstrated that the chimeric benefit is dependent on a holistic representation of the face. Finally, in Experiment 4, we showed that the positive contrast eye region needs to match the identity of the contrast negated part of the image for the chimera benefit to occur. Together, these results show the importance of the eye region for holistic representations of facial identity.

Monte Carlo simulations were performed in order to obtain reflectance measurements from phantoms typically used in biomedical optics when either unpolarized or circularly polarized incident light is used. Phantoms contain spherical targets of different diameters, placed at different depths, with higher absorption than the surrounding medium, which are detected using a coaxial setup of laser and detector. The considered turbid media have highly anisotropic scattering phase functions, so detected light for the considered times of flight is not diffuse, but rather in the multiple-scattering regime. Therefore, the target reconstruction methods typically used in diffuse optical imaging cannot be employed. However, spatially resolved reflectance measurements in the time domain allow use of a novel reconstruction method based on the approximation of average photon trajectories, which are functions of the separation distance from the point of incidence and of the time of flight. With the approximated average photon trajectories, one can estimate the depth of the target.

Targeting of permissive entry sites is crucial for bacterial infection. The targeting mechanisms are incompletely understood. We have analyzed target-site selection by S. Typhimurium. This enteropathogenic bacterium employs adhesins (e.g. fim) and the type III secretion system 1 (TTSS-1) for host cell binding, the triggering of ruffles and invasion. Typically, S. Typhimurium invasion is focused on a subset of cells and multiple bacteria invade via the same ruffle. It has remained unclear how this is achieved. We have studied target-site selection in tissue culture by time lapse microscopy, movement pattern analysis and modeling. Flagellar motility (but not chemotaxis) was required for reaching the host cell surface in vitro. Subsequently, physical forces trapped the pathogen for ∼1.5-3 s in "near surface swimming". This increased the local pathogen density and facilitated "scanning" of the host surface topology. We observed transient TTSS-1 and fim-independent "stopping" and irreversible TTSS-1-mediated docking, in particular at sites of prominent topology, i.e. the base of rounded-up cells and membrane ruffles. Our data indicate that target site selection and the cooperative infection of membrane ruffles are attributable to near surface swimming. This mechanism might be of general importance for understanding infection by flagellated bacteria.

In this paper a new approach to improve contrast in optical subsurface imaging is presented. The method is based on time-resolved reflectance and selection of ballistic photons using polarization gating. Numerical studies with a statistical Monte Carlo method also reveal that weakly scattered diffuse photons can be eliminated by employing a small aperture and that the contrast improvement strongly depends on the single-scattering phase function. A possible experimental setup is discussed in the conclusions.

Birefringent media, like biological tissues, are usually assumed to be uniaxial. For biological tissues, the influence of linear birefringence on the scattering phase function is assumed to be neglectable. In order to examine this, a numerical study of the influence of linear birefringence on the scattering phase function and the resulting backscattering Mueller matrices was performed. It is assumed that the media consist of spherical scattering particles embedded in a nonabsorbing medium, which allows us to employ the Lorenz-Mie theory. In the Monte Carlo framework, the influence of linear birefringence on the components of the electric field vector is captured through the Jones N-matrix formalism. The Lorenz-Mie theory indicates that a given linear birefringence value Δn has a bigger impact on the scattering phase function for large particles. This conclusion is further supported by Monte Carlo simulations, where the phase function was calculated based on the refractive index once in the ordinary direction and once in the extraordinary one. For large particles, comparisons of the resulting backscattering Mueller matrices show significant differences even for small Δn values.

This paper deals with an efficient and accurate simulation algorithm to solve the vector Boltzmann equation for polarized light transport in scattering media. The approach is based on a stencil method, which was previously developed for unpolarized light scattering and proved to be much more efficient (speedup factors of up to 10 were reported) than the classical Monte Carlo while being equally accurate. To validate what we believe to be the new stencil method, a substrate composed of spherical non-absorbing particles embedded in a non-absorbing medium was considered. The corresponding single scattering Mueller matrix, which is required to model scattering of polarized light, was determined based on the Lorenz-Mie theory. From simulations of a reflected polarized laser beam, the Mueller matrix of the substrate was computed and compared with an established reference. The agreement is excellent, and it could be demonstrated that a significant speedup of the simulations is achieved due to the stencil approach compared with the classical Monte Carlo.

This work deals with the efficient and accurate modeling of fluorescence in the context of stochastic Monte Carlo methods for which we propose a novel multiscale method. As in other approaches of this category, the transport theory is employed to describe the physics. The new framework was successfully applied for a quantitative assessment of halftone reflectance measurements with three different devices. It could be demonstrated that the described method is faster than classical Monte Carlo by multiple orders of magnitude, and that it is capable of correctly handling the geometrical device differences. It is also shown that optical dot gain is accurately predicted for the whole ink coverage range.