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Annual Review of Psychology 2013Executive functions (EFs) make possible mentally playing with ideas; taking the time to think before acting; meeting novel, unanticipated challenges; resisting... (Review)
Review
Executive functions (EFs) make possible mentally playing with ideas; taking the time to think before acting; meeting novel, unanticipated challenges; resisting temptations; and staying focused. Core EFs are inhibition [response inhibition (self-control--resisting temptations and resisting acting impulsively) and interference control (selective attention and cognitive inhibition)], working memory, and cognitive flexibility (including creatively thinking "outside the box," seeing anything from different perspectives, and quickly and flexibly adapting to changed circumstances). The developmental progression and representative measures of each are discussed. Controversies are addressed (e.g., the relation between EFs and fluid intelligence, self-regulation, executive attention, and effortful control, and the relation between working memory and inhibition and attention). The importance of social, emotional, and physical health for cognitive health is discussed because stress, lack of sleep, loneliness, or lack of exercise each impair EFs. That EFs are trainable and can be improved with practice is addressed, including diverse methods tried thus far.
Topics: Attention; Cognition; Executive Function; Humans; Inhibition, Psychological; Intelligence; Memory, Short-Term
PubMed: 23020641
DOI: 10.1146/annurev-psych-113011-143750 -
Nature Reviews. Genetics Mar 2018Intelligence - the ability to learn, reason and solve problems - is at the forefront of behavioural genetic research. Intelligence is highly heritable and predicts... (Review)
Review
Intelligence - the ability to learn, reason and solve problems - is at the forefront of behavioural genetic research. Intelligence is highly heritable and predicts important educational, occupational and health outcomes better than any other trait. Recent genome-wide association studies have successfully identified inherited genome sequence differences that account for 20% of the 50% heritability of intelligence. These findings open new avenues for research into the causes and consequences of intelligence using genome-wide polygenic scores that aggregate the effects of thousands of genetic variants.
Topics: Genome-Wide Association Study; Human Genetics; Humans; Intelligence; Polymorphism, Single Nucleotide; Quantitative Trait, Heritable
PubMed: 29335645
DOI: 10.1038/nrg.2017.104 -
Dialogues in Clinical Neuroscience Mar 2012Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional... (Review)
Review
Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex-and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret.
Topics: Cognition; Humans; Intelligence; Intelligence Tests; Memory, Episodic; Models, Psychological
PubMed: 22577301
DOI: 10.31887/DCNS.2012.14.1/rsternberg -
Neuron Jul 2017The fields of neuroscience and artificial intelligence (AI) have a long and intertwined history. In more recent times, however, communication and collaboration between... (Review)
Review
The fields of neuroscience and artificial intelligence (AI) have a long and intertwined history. In more recent times, however, communication and collaboration between the two fields has become less commonplace. In this article, we argue that better understanding biological brains could play a vital role in building intelligent machines. We survey historical interactions between the AI and neuroscience fields and emphasize current advances in AI that have been inspired by the study of neural computation in humans and other animals. We conclude by highlighting shared themes that may be key for advancing future research in both fields.
Topics: Animals; Artificial Intelligence; Brain; Humans; Intelligence; Learning; Neural Networks, Computer; Neurosciences
PubMed: 28728020
DOI: 10.1016/j.neuron.2017.06.011 -
Biosensors Jul 2022Artificial intelligence (AI) is a modern approach based on computer science that develops programs and algorithms to make devices intelligent and efficient for... (Review)
Review
Artificial intelligence (AI) is a modern approach based on computer science that develops programs and algorithms to make devices intelligent and efficient for performing tasks that usually require skilled human intelligence. AI involves various subsets, including machine learning (ML), deep learning (DL), conventional neural networks, fuzzy logic, and speech recognition, with unique capabilities and functionalities that can improve the performances of modern medical sciences. Such intelligent systems simplify human intervention in clinical diagnosis, medical imaging, and decision-making ability. In the same era, the Internet of Medical Things (IoMT) emerges as a next-generation bio-analytical tool that combines network-linked biomedical devices with a software application for advancing human health. In this review, we discuss the importance of AI in improving the capabilities of IoMT and point-of-care (POC) devices used in advanced healthcare sectors such as cardiac measurement, cancer diagnosis, and diabetes management. The role of AI in supporting advanced robotic surgeries developed for advanced biomedical applications is also discussed in this article. The position and importance of AI in improving the functionality, detection accuracy, decision-making ability of IoMT devices, and evaluation of associated risks assessment is discussed carefully and critically in this review. This review also encompasses the technological and engineering challenges and prospects for AI-based cloud-integrated personalized IoMT devices for designing efficient POC biomedical systems suitable for next-generation intelligent healthcare.
Topics: Artificial Intelligence; Delivery of Health Care; Humans; Intelligence; Internet of Things; Neural Networks, Computer
PubMed: 35892459
DOI: 10.3390/bios12080562 -
Molecular Psychiatry Jan 2022Individual differences in human intelligence, as assessed using cognitive test scores, have a well-replicated, hierarchical phenotypic covariance structure. They are... (Review)
Review
Individual differences in human intelligence, as assessed using cognitive test scores, have a well-replicated, hierarchical phenotypic covariance structure. They are substantially stable across the life course, and are predictive of educational, social, and health outcomes. From this solid phenotypic foundation and importance for life, comes an interest in the environmental, social, and genetic aetiologies of intelligence, and in the foundations of intelligence differences in brain structure and functioning. Here, we summarise and critique the last 10 years or so of molecular genetic (DNA-based) research on intelligence, including the discovery of genetic loci associated with intelligence, DNA-based heritability, and intelligence's genetic correlations with other traits. We summarise new brain imaging-intelligence findings, including whole-brain associations and grey and white matter associations. We summarise regional brain imaging associations with intelligence and interpret these with respect to theoretical accounts. We address research that combines genetics and brain imaging in studying intelligence differences. There are new, though modest, associations in all these areas, and mechanistic accounts are lacking. We attempt to identify growing points that might contribute toward a more integrated 'systems biology' account of some of the between-individual differences in intelligence.
Topics: Brain; Genetic Variation; Humans; Intelligence; Neuropsychological Tests; White Matter
PubMed: 33531661
DOI: 10.1038/s41380-021-01027-y -
The Journal of Medical Investigation :... 2017The coexistence of technology and caring is best exemplified in nursing. The theory of Technological Competency as Caring in Nursing illuminates this coexistence as the...
The coexistence of technology and caring is best exemplified in nursing. The theory of Technological Competency as Caring in Nursing illuminates this coexistence as the essence of technology in health care premised on machine technologies as a generic concept of objects or things that are mechanical, organic, and electronic. With its timely development these technologies are continually imbued with artificial general intelligence. As such, the ultimate expression of machine technologies in nursing turns out to be autonomous robots (ARs) with future potentials of functions comparable to human persons. While theory-based nursing practice is essential to nursing care practice, quality human care, particularly with technologies assuming indispensable practice process mechanisms is critical. Some practice-based questions informing ARs and human person engagements in nursing care practice include, "Will ARs which are imbued with artificial intelligence replace nurses in their practice?" "What contributions to quality human health care will autonomous and artificially intelligent robots provide?" While these questions may reflect far-reaching ramifications of technologies in health care, it must also be acknowledged that these technologies are fundamental to the delivery of quality human health care now, and in the future. J. Med. Invest. 64: 160-164, February, 2017.
Topics: Biomedical Technology; Empathy; Humans; Nursing Care; Nursing Theory; Robotics
PubMed: 28373615
DOI: 10.2152/jmi.64.160 -
Neural Networks : the Official Journal... Dec 2021Understanding information processing in the brain-and creating general-purpose artificial intelligence-are long-standing aspirations of scientists and engineers... (Review)
Review
Understanding information processing in the brain-and creating general-purpose artificial intelligence-are long-standing aspirations of scientists and engineers worldwide. The distinctive features of human intelligence are high-level cognition and control in various interactions with the world including the self, which are not defined in advance and are vary over time. The challenge of building human-like intelligent machines, as well as progress in brain science and behavioural analyses, robotics, and their associated theoretical formalisations, speaks to the importance of the world-model learning and inference. In this article, after briefly surveying the history and challenges of internal model learning and probabilistic learning, we introduce the free energy principle, which provides a useful framework within which to consider neuronal computation and probabilistic world models. Next, we showcase examples of human behaviour and cognition explained under that principle. We then describe symbol emergence in the context of probabilistic modelling, as a topic at the frontiers of cognitive robotics. Lastly, we review recent progress in creating human-like intelligence by using novel probabilistic programming languages. The striking consensus that emerges from these studies is that probabilistic descriptions of learning and inference are powerful and effective ways to create human-like artificial intelligent machines and to understand intelligence in the context of how humans interact with their world.
Topics: Artificial Intelligence; Brain; Cognition; Humans; Intelligence; Models, Statistical
PubMed: 34634605
DOI: 10.1016/j.neunet.2021.09.011 -
Sensors (Basel, Switzerland) Nov 2022Advanced intelligent vehicle control systems have evolved in the last few decades thanks to the use of artificial-intelligence-based techniques, the appearance of new...
Advanced intelligent vehicle control systems have evolved in the last few decades thanks to the use of artificial-intelligence-based techniques, the appearance of new sensors, and the development of technology necessary for their implementation [...].
Topics: Artificial Intelligence; Intelligence
PubMed: 36433219
DOI: 10.3390/s22228622 -
Journal of the Royal Society, Interface Mar 2023We develop a conceptual framework for studying collective adaptation in complex socio-cognitive systems, driven by dynamic interactions of social integration strategies,... (Review)
Review
We develop a conceptual framework for studying collective adaptation in complex socio-cognitive systems, driven by dynamic interactions of social integration strategies, social environments and problem structures. Going beyond searching for 'intelligent' collectives, we integrate research from different disciplines and outline modelling approaches that can be used to begin answering questions such as why collectives sometimes fail to reach seemingly obvious solutions, how they change their strategies and network structures in response to different problems and how we can anticipate and perhaps change future harmful societal trajectories. We discuss the importance of considering path dependence, lack of optimization and collective myopia to understand the sometimes counterintuitive outcomes of collective adaptation. We call for a transdisciplinary, quantitative and societally useful social science that can help us to understand our rapidly changing and ever more complex societies, avoid collective disasters and reach the full potential of our ability to organize in adaptive collectives.
Topics: Intelligence; Social Environment
PubMed: 36946092
DOI: 10.1098/rsif.2022.0736