We provide empirical examples to conceptually clarify some items on Firestone & Scholl’s (F&S’s) checklist, and to explain perceptual effects from an attentional and memory perspective. We also note that action and embodied cognition studies seem to be most susceptible to misattributing attentional and memory effects as perceptual, and identify four characteristics unique to action studies and possibly responsible for misattributions.

Given the sordid history of injustices linking genetics to race and ethnicity, considerations of justice are central to ensuring the responsible development of precision medicine programmes around the world. While considerations of justice may be in tension with other areas of concern, such as scientific value or privacy, there are also tensions between different aspects of justice. This paper focuses on three particular aspects of justice relevant to this precision medicine: social justice, distributive justice and human rights. We describe the (...) implications of each for the use of race and ethnicity in precision medicine, and also how they intersect and potentially conflict with each another. By attending to these intersections, we aim to enrich and add nuance to debates over how best to proceed with precision medicine initiatives. (shrink)

Ethical decision-making frameworks assist in identifying the issues at stake in a particular setting and thinking through, in a methodical manner, the ethical issues that require consideration as well as the values that need to be considered and promoted. Decisions made about the use, sharing, and re-use of big data are complex and laden with values. This paper sets out an Ethics Framework for Big Data in Health and Research developed by a working group convened by the Science, Health and (...) Policy-relevant Ethics in Singapore Initiative. It presents the aim and rationale for this framework supported by the underlying ethical concerns that relate to all health and research contexts. It also describes a set of substantive and procedural values that can be weighed up in addressing these concerns, and a step-by-step process for identifying, considering, and resolving the ethical issues arising from big data uses in health and research. This Framework is subsequently applied in the papers published in this Special Issue. These papers each address one of six domains where big data is currently employed: openness in big data and data repositories, precision medicine and big data, real-world data to generate evidence about healthcare interventions, AI-assisted decision-making in healthcare, public-private partnerships in healthcare and research, and cross-sectoral big data. (shrink)

As opposed to a ‘one size fits all’ approach, precision medicine uses relevant biological, medical, behavioural and environmental information about a person to further personalize their healthcare. This could mean better prediction of someone’s disease risk and more effective diagnosis and treatment if they have a condition. Big data allows for far more precision and tailoring than was ever before possible by linking together diverse datasets to reveal hitherto-unknown correlations and causal pathways. But it also raises ethical issues relating to (...) the balancing of interests, viability of anonymization, familial and group implications, as well as genetic discrimination. This article analyses these issues in light of the values of public benefit, justice, harm minimization, transparency, engagement and reflexivity and applies the deliberative balancing approach found in theEthical Framework for Big Data in Health and Research to a case study on clinical genomic data sharing. Please refer to that article for an explanation of how this framework is to be used, including a full explanation of the key values involved and the balancing approach used in the case study at the end. Our discussion is meant to be of use to those involved in the practice as well as governance and oversight of precision medicine to address ethical concerns that arise in a coherent and systematic manner. (shrink)

Following the pioneering studies of the receptive field (RF), the concept gained further significance for visual perception by the discovery of input effects from beyond the classical RF. These studies demonstrated that neuronal responses could be modulated by stimuli outside their RFs, consistent with the perception of induced brightness, color, orientation, and motion. Lesion scotomata are similarly modulated perceptually from the surround by RFs that have migrated from the interior to the outer edge of the scotoma and in this way (...) provide filling-in of the void. Large RFs are advantageous to this task. In higher visual areas, such as the middle temporal and inferotemporal lobe, RFs increase in size and lose most of their retinotopic organization while encoding increasingly complex features. Whereas lowerlevel RFs mediate perceptual filling-in, contour integration, and figure–ground segregation, RFs at higher levels serve the perception of grouping by common fate, biological motion, and other biologically relevant stimuli, such as faces. Studies in alert monkeys while freely viewing natural scenes showed that classical and nonclassical RFs cooperate in forming representations of the visual world. Today, our understanding of the mechanisms underlying the RF is undergoing a quantum leap. What had started out as a hierarchical feedforward concept for simple stimuli, such as spots, lines, and bars, now refers to mechanisms involving ascending, descending, and lateral signal flow. By extension of the bottom-up paradigm, RFs are nowadays understood as adaptive processors, enabling the predictive coding of complex scenes. Top-down effects guiding attention and tuned to task-relevant information complement the bottom-up analysis. (shrink)