An exploration of reciprocity between female athletes and their coach in elite junior swimming: a shared reality theory perspective

Based on the proposition that the relationship between a coach and athlete is at its best when both parties contribute to enhancing its quality, the present study sought to investigate if Shared Reality Theory could provide new insights on the topic. Specifically, the purpose of the present study was to explore: (a) how a shared reality is established, or fails to be established, over the course of the sporting partnership between athletes and their coach; and (b) how the presence of a shared reality (or not) in the coach-athlete relationship is related to the experienced quality of the relationship between athletes and their coach, as recorded over time. Narrative inquiry, embedded within a longitudinal qualitative approach, was adopted. Six female elite junior swimmers and their head coach completing three interviews each over a 9-month period. Data were analysed using narrative thematic analysis, leading to the development of two narratives: A prevention-oriented narrative and a promotion-oriented narrative. Overall, the findings suggests that athletes who experience a shared reality with their coach are more motivated and report a higher sense of psychological well-being. To establish the experience of a shared reality, reciprocal and honest communication motivated by trust in the other is needed. Due to power imbalance, it is deemed important for coaches to be supportive and trustworthy to encourage athletes to communicate with them, so the coach and his/her athletes can work together in a synergistic manner

The experience of laser light feedback in back-squat resistance training

IntroductionThe purpose of this paper is to contribute to the existing literature on performance in resistance training (RT) by addressing how a phenomenological perspective on experiences with inter kinaesthetic affectivity can illuminate experience of practicing RT with non-verbal, visual feedback provided through laser lights attached to the barbell.MethodThe material is created from qualitative interviews and using inter-kinaesthetic affectivity as analytical lenses.ResultsThe findings show how participants interpret the feedback in the moment and explain how they adjust their movement in dialogue with the feedback and enable the “uptake” of feedback in their embodied experience. The findings show how the participants developed an awareness of how they can equalize the balance on their feet.DiscussionWe discuss what this means for the understanding of the training process in terms of how practitioners can use the uptake of non-verbal, visual feedback to immediately adjust the quality of their performance by responding kinaesthetically and bodily. The discussion contributes to the question of what kind of role a practitioner's own kinaesthetic and bodily experiences have in the development and organization of RT. Perspectives that include the lived and intersubjective body as a knowledge position are promising for illuminating the whole bodied engagement that is necessary to understand how to perform RT

Organizing Shared Digital Reading in Groups: Optimizing the Affordances of Text and Medium

Children develop their language when they explore and talk about literary texts. In this study, we explore the design of shared digital reading as a basis for critical reflection on the reading situation in an institutional context with its given opportunities and limitations. We examine six videotaped readings of one specific picture book app, with a focus on the strategies used by teachers in early childhood education and care institutions to control children’s access to the medium and the types of verbal engagement (about the story and about the medium) that are generated by these different strategies. We use qualitative and quantitative analysis of video data. A qualitative categorization of the readings reveals the strategies Show, Show & Share, and Share. In analyzing the participants’ verbal and multisensory engagement, we find that the Show strategy generates more utterances, especially about the story, as well as more time spent on dialogue.publishedVersio

Differential influences of environment and self-motion on place and grid cell firing

Place and grid cells in the hippocampal formation provide foundational representations of environmental location, and potentially of locations within conceptual spaces. Some accounts predict that environmental sensory information and self-motion are encoded in complementary representations, while other models suggest that both features combine to produce a single coherent representation. Here, we use virtual reality to dissociate visual environmental from physical motion inputs, while recording place and grid cells in mice navigating virtual open arenas. Place cell firing patterns predominantly reflect visual inputs, while grid cell activity reflects a greater influence of physical motion. Thus, even when recorded simultaneously, place and grid cell firing patterns differentially reflect environmental information (or ‘states’) and physical self-motion (or ‘transitions’), and need not be mutually coherent

Modeling Boundary Vector Cell Firing Given Optic Flow as a Cue

Boundary vector cells in entorhinal cortex fire when a rat is in locations at a specific distance from walls of an environment. This firing may originate from memory of the barrier location combined with path integration, or the firing may depend upon the apparent visual input image stream. The modeling work presented here investigates the role of optic flow, the apparent change of patterns of light on the retina, as input for boundary vector cell firing. Analytical spherical flow is used by a template model to segment walls from the ground, to estimate self-motion and the distance and allocentric direction of walls, and to detect drop-offs. Distance estimates of walls in an empty circular or rectangular box have a mean error of less than or equal to two centimeters. Integrating these estimates into a visually driven boundary vector cell model leads to the firing patterns characteristic for boundary vector cells. This suggests that optic flow can influence the firing of boundary vector cells

Spontaneous Reorientation Is Guided by Perceived Surface Distance, Not by Image Matching Or Comparison

Humans and animals recover their sense of position and orientation using properties of the surface layout, but the processes underlying this ability are disputed. Although behavioral and neurophysiological experiments on animals long have suggested that reorientation depends on representations of surface distance, recent experiments on young children join experimental studies and computational models of animal navigation to suggest that reorientation depends either on processing of any continuous perceptual variables or on matching of 2D, depthless images of the landscape. We tested the surface distance hypothesis against these alternatives through studies of children, using environments whose 3D shape and 2D image properties were arranged to enhance or cancel impressions of depth. In the absence of training, children reoriented by subtle differences in perceived surface distance under conditions that challenge current models of 2D-image matching or comparison processes. We provide evidence that children’s spontaneous navigation depends on representations of 3D layout geometry.National Institutes of Health (U.S.) (Grant HD 23103

Accurate path integration in continuous attractor network models of grid cells

Grid cells in the rat entorhinal cortex display strikingly regular firing responses to the animal's position in 2-D space and have been hypothesized to form the neural substrate for dead-reckoning. However, errors accumulate rapidly when velocity inputs are integrated in existing models of grid cell activity. To produce grid-cell-like responses, these models would require frequent resets triggered by external sensory cues. Such inadequacies, shared by various models, cast doubt on the dead-reckoning potential of the grid cell system. Here we focus on the question of accurate path integration, specifically in continuous attractor models of grid cell activity. We show, in contrast to previous models, that continuous attractor models can generate regular triangular grid responses, based on inputs that encode only the rat's velocity and heading direction. We consider the role of the network boundary in the integration performance of the network and show that both periodic and aperiodic networks are capable of accurate path integration, despite important differences in their attractor manifolds. We quantify the rate at which errors in the velocity integration accumulate as a function of network size and intrinsic noise within the network. With a plausible range of parameters and the inclusion of spike variability, our model networks can accurately integrate velocity inputs over a maximum of ~10–100 meters and ~1–10 minutes. These findings form a proof-of-concept that continuous attractor dynamics may underlie velocity integration in the dorsolateral medial entorhinal cortex. The simulations also generate pertinent upper bounds on the accuracy of integration that may be achieved by continuous attractor dynamics in the grid cell network. We suggest experiments to test the continuous attractor model and differentiate it from models in which single cells establish their responses independently of each other

Repeatability of Corticospinal and Spinal Measures during Lengthening and Shortening Contractions in the Human Tibialis Anterior Muscle

Elements of the human central nervous system (CNS) constantly oscillate. In addition, there are also methodological factors and changes in muscle mechanics during dynamic muscle contractions that threaten the stability and consistency of transcranial magnetic stimulation (TMS) and perpherial nerve stimulation (PNS) measures

Grid Cells, Place Cells, and Geodesic Generalization for Spatial Reinforcement Learning

Reinforcement learning (RL) provides an influential characterization of the brain's mechanisms for learning to make advantageous choices. An important problem, though, is how complex tasks can be represented in a way that enables efficient learning. We consider this problem through the lens of spatial navigation, examining how two of the brain's location representations—hippocampal place cells and entorhinal grid cells—are adapted to serve as basis functions for approximating value over space for RL. Although much previous work has focused on these systems' roles in combining upstream sensory cues to track location, revisiting these representations with a focus on how they support this downstream decision function offers complementary insights into their characteristics. Rather than localization, the key problem in learning is generalization between past and present situations, which may not match perfectly. Accordingly, although neural populations collectively offer a precise representation of position, our simulations of navigational tasks verify the suggestion that RL gains efficiency from the more diffuse tuning of individual neurons, which allows learning about rewards to generalize over longer distances given fewer training experiences. However, work on generalization in RL suggests the underlying representation should respect the environment's layout. In particular, although it is often assumed that neurons track location in Euclidean coordinates (that a place cell's activity declines “as the crow flies” away from its peak), the relevant metric for value is geodesic: the distance along a path, around any obstacles. We formalize this intuition and present simulations showing how Euclidean, but not geodesic, representations can interfere with RL by generalizing inappropriately across barriers. Our proposal that place and grid responses should be modulated by geodesic distances suggests novel predictions about how obstacles should affect spatial firing fields, which provides a new viewpoint on data concerning both spatial codes