China
Africa
Explore chapters and articles related to this topic
Cognitive Science: Integrative Theory of Cognition, Cognitivism and Computationalism
Published in Harald Maurer, Cognitive Science, 2021
This chapter introduces the basic concepts, statements, subject area and methods of cognitive science (chap. 1.1, 1.3 and 1.5), including a list of cognitive science's subdisciplines (chap. 1.2). This will provide the background needed to adequately address the two main alternative approaches to a theory of cognition in cognitive science: the classical symbol theory (chap. 3.1) and the connectionist theory (chap. 3.2). The basic assumption is that a theory of neurocognition - in its structural core - can best be described by mathematical and logical computation operations. Finally, the goal of this introductory book in connectionist cognitive science is to present a comprehensive and appropriate theory of neurocognition in modern (system-theoretical) connectionism (chap. 1.4). This means that this book primarily takes account of empirical evidence from the cognitive neurosciences (chap. 4) and the theoretical concepts of neuroinformatics and computational neuroscience (chaps. 6-10), and is oriented towards them.
Ellen R. Grass Lecture: The Future of Neurodiagnostics and Emergence of a New Science
Published in The Neurodiagnostic Journal, 2023
Health is a multidimensional and complicated construct. The importance of mental and neurological health as a dimension for personalized or precision health care is becoming increasingly apparent. The confluence of new developments in neurotechnology, cognitive and neuroscience, complex dynamical systems theory, and biomedical informatics is giving birth to a new science of clinical neuroinformatics. This new science is the foundation for fundamental advances in our understanding of the brain-behavior or brain-mind relationships. It is also the foundation and driving force for a much greater clinical role for neurodiagnostics in precision medicine or learning health care systems. Clinical neuroinformatics professionals will be needed to discover and implement ways to integrate brain data into a multidimensional view of health and disease. It is hoped that this paper will be a catalyst for the creation and advance of the new science of clinical neuroinformatics, the formation of a new interprofessional special interest group, and the establishment of guidelines for new graduate level programs to train leaders in this field. The future for neurodiagnostic professionals has never been brighter.
The Emerging Role of Neurodiagnostic Informatics in Integrated Neurological and Mental Health Care
Published in The Neurodiagnostic Journal, 2018
The simultaneous emergence of portable, efficient EEG hardware, electronic medical records, nonlinear methods for analyzing complex systems, and systems neuroscience has created a remarkable opportunity for creation of a new paradigm for early detection and treatment of mental, neurological, and neurodevelopmental disorders. The combination of skills that will be needed to take these disparate research results to the clinic as a unified clinical support technology for practicing clinicians includes neurodiagnostics, neurology, psychiatry, and biomedical informatics. An opportunity is emerging for the next generation of neurodiagnostic technologists to obtain advanced training in biomedical informatics and clinical neurophysiology, applying this integrated, advanced training to the creation of digital biomarkers to monitor the brain for psychiatric and neurological disorders. This new field is still awaiting definition but may be called “neuroinformatics” or “neurodiagnostic informatics,” indicating the critical integration of neurotechnology, clinical neuroscience, and information technology. This is a natural evolution of EEG technology with biomedical informatics and information technology. Before the genomic revolution was possible, mathematical and computational tools for analyzing nucleotide sequences from DNA were required to make sense of the new data source. Similarly, computational methods for analyzing EEG signals will be required to make EEG fully useful for new applications.