Understanding mental processes in biological terms makes available insights from the new science of the mind to explore connections between philosophy, psychology, the social sciences, the humanities, and studies of disorders of mind. In this perspective we examine how these linkages might be forged and how the new science of the mind might serve as an inspiration for further exploration.
We have seen in this essay four specific areas in which the new science of the mind is particularly well positioned to enrich our understanding of other areas of knowledge. We have seen its potential as an intellectual force and a font of new knowledge that is likely to bring about a new dialog between the natural sciences, the social sciences, and the humanities. This dialog could help us understand better the mechanisms in the brain that make creativity possible, whether in art, the sciences, or the humanities, and thus open up a new dimension in intellectual history. In addition, an enriched understanding of the brain is needed to guide public policy. Particularly promising areas are the cognitive and emotional development of infants, the improvement of teaching methods, and the evaluation of decisions. But perhaps the greatest consequence for public policy is the impact that brain science and its engagement with other disciplines is likely to have on the structure of the social universe as we know it.
The developments in the communication and networking technologies have yielded many existing and envisioned information network architectures such as cognitive radio networks, sensor and actor networks, quantum communication networks, terrestrial next generation Internet, and InterPlaNetary Internet. However, there exist many common significant challenges to be addressed for the practical realization of these current and envisioned networking paradigms such as the increased complexity with large scale networks, their dynamic nature, resource constraints, heterogeneous architectures, absence or impracticality of centralized control and infrastructure, need for survivability, and unattended resolution of potential failures. These challenges have been successfully dealt with by Nature, which, as a result of millions of years of evolution, have yielded many biological systems and processes with intrinsic appealing characteristics such as adaptivity to varying environmental conditions, inherent resiliency to failures and damages, successful and collaborative operation on the basis of a limited set of rules and with global intelligence which is larger than superposition of individuals, self-organization, survivability, and evolvability. Inspired by these characteristics, many researchers are currently engaged in developing innovative design paradigms to address the networking challenges of existing and envisioned information systems. In this paper, the current state-of-the-art in bio-inspired networking is captured. The existing bio-inspired networking and communication protocols and algorithms devised by looking at biology as a source of inspiration, and by mimicking the laws and dynamics governing these systems are presented along with open research issues for the bio-inspired networking. Furthermore, the domain of bio-inspired networking is linked to the emerging research domain of nano networks, which bring a set of unique challenges. The objective of this survey is to provide better understanding of the potentials for bio-inspired networking which is currently far from being fully recognized, and to motivate the research community to further explore this timely and exciting topic.
Human behavior is remarkably variable. It changes systematically over time, and it fluctuates moment-to-moment depending on the immediate context. If this kind of individual variability is ignored or marginalized, it acts asnoise disguising the dynamic nature of individual behavior and growth, and it will often mislead researchers. In contrast, starting with a focus on individual variability, rather than statistical averages, leads to new, elegant explanations for the richness of behavior, including models and methods for analyzing variability over time and across contexts. These concepts and tools help more closely align theory, research, and practice, and give us the best opportunity to develop usable knowledge about the complex and variable ways that individuals behave, learn, and grow.
Our goal is to establish a science of the individual, grounded in dynamic systems, and focused on the analysis of individual variability. Our argument is that individuals behave, learn, and develop in distinctive ways, showing patterns of variability that are not captured by models based on statistical averages. As such, any meaningful attempt to develop a science of the individual necessarily begins with an account of the individual variability that is pervasive in all aspects of behavior, and at all levels of analysis. Using examples from fields as diverse as education and medicine, we show how starting with individual variability, not statistical averages, helped researchers discover two sources of ordered variability — pathways and contexts — that have implications for theory, research, and practice in multiple disciplines. We conclude by discussing three broad challenges—data, models, and the nature of science—that must be addressed to ensure that the science of the individual reaches its full potential.
Se basant sur les neurosciences, l’auteur passe successivement en revue divers problèmes relatifs à la décision: décision et raison, décision et regard, décision et inhibition, décision et double, décision et anticipation, décision et émotion, décision et interactions ou normes sociales (compétition entre émotion et cognition, changement de point de vue, sympathie et empathie). Il conclut son exposé en soulignant que dans tous ces processus neurophysiologiques et psychologiques extrêmement complexes et interactifs, il faut tenir compte en plus des différences interindividuelles liées à l’âge, l’expérience, le sexe.
Virtually all domains of cognitive function require the integration of distributed neural activity. Network analysis of human brain connectivity has consistently identified sets of regions that are critically important for enabling efficient neuronal signaling and communication. The central embedding of these candidate ‘brain hubs’ in anatomical networks supports their diverse functional roles across a broad range of cognitive tasks and widespread dynamic coupling within and across functional networks. The high level of centrality of brain hubs also renders them points of vulnerability that are susceptible to disconnection and dysfunction in brain disorders. Combining data from numerous empirical and computational studies, network approaches strongly suggest that brain hubs play important roles in information integration underpinning numerous aspects of complex cognitive function.
Network approaches to neuroscience are currently accelerating at a rapid pace, propelled by the availability of ‘big data’, an expanding computational infrastructure, and the formation of large-scale research consortia and initiatives focused on mapping brain connectivity. As these developments unfold, it seems certain that the study of brain network hubs will remain an enduring theme in the quest to better understand the complex function of the human brain.