Posts Tagged ‘cognitive neuroscience’
Socioeconomic disparities are associated with differences in cognitive development. The extent to which this translates to disparities in brain structure is unclear. We investigated relationships between socioeconomic factors and brain morphometry, independently of genetic ancestry, among a cohort of 1,099 typically developing individuals between 3 and 20 years of age. Income was logarithmically associated with brain surface area. Among children from lower income families, small differences in income were associated with relatively large differences in surface area, whereas, among children from higher income families, similar income increments were associated with smaller differences in surface area. These relationships were most prominent in regions supporting language, reading, executive functions and spatial skills; surface area mediated socioeconomic differences in certain neurocognitive abilities. These data imply that income relates most strongly to brain structure among the most disadvantaged children.
Curiosity is a basic element of our cognition, but its biological function, mechanisms, and neural underpinning remain poorly understood. It is nonetheless a motivator for learning, influential in decision-making, and crucial for healthy development. One factor limiting our understanding of it is the lack of a widely agreed upon delineation of what is and is not curiosity. Another factor is the dearth of standardized laboratory tasks that manipulate curiosity in the lab. Despite these barriers, recent years have seen a major growth of interest in both the neuroscience and psychology of curiosity. In this Perspective, we advocate for the importance of the field, provide a selective overview of its current state, and describe tasks that are used to study curiosity and information-seeking. We propose that, rather than worry about defining curiosity, it is more helpful to consider the motivations for information-seeking behavior and to study it in its ethological context.
This book presents a unique synthesis of the current neuroscience of cognition by one of the world’s authorities in the field. The guiding principle to this synthesis is the tenet that the entirety of our knowledge is encoded by relations, and thus by connections, in neuronal networks of our cerebral cortex. Cognitive networks develop by experience on a base of widely dispersed modular cell assemblies representing elementary sensations and movements. As they develop cognitive networks organize themselves hierarchically by order of complexity or abstraction of their content. Because networks intersect profusely, a neuronal assembly anywhere in the cortex can be part of many networks, and therefore many items of knowledge. All cognitive functions consist of neural transactions within and between cognitive networks. After reviewing the neurobiology and architecture of cortical networks (also named cognits), the author undertakes a systematic study of cortical dynamics in each of the major cognitive functions–perception, memory, attention, language, and intelligence. In this study, he makes use of a large body of evidence from a variety of methodologies, in the brain of the human as well as the nonhuman primate. The outcome of his interdisciplinary endeavor is the emergence of a structural and dynamic order in the cerebral cortex that, though still sketchy and fragmentary, mirrors with remarkable fidelity the order in the human mind.
Most accounts of human cognitive architectures have focused on computational accounts of cognition while making little contact with the study of anatomical structures and physiological processes. A renewed convergence between neurobiology and cognition is well under way. A promising area arises from the overlap between systems/cognitive neuroscience on the one side and the discipline of network science on the other. Neuroscience increasingly adopts network tools and concepts to describe the operation of collections of brain regions. Beyond just providing illustrative metaphors, network science offers a theoretical framework for approaching brain structure and function as a multi-scale system composed of networks of neurons, circuits, nuclei, cortical areas, and systems of areas. This paper views large-scale networks at the level of areas and systems, mostly on the basis of data from human neuroimaging, and how this view of network structure and function has begun to illuminate our understanding of the biological basis of cognitive architectures.
People find it easier to learn about topics that interest them, but little is known about the mechanisms by which intrinsic motivational states affect learning. We used functional magnetic resonance imaging to investigate how curiosity (intrinsic motivation to learn) influences memory. In both immediate and one-day-delayed memory tests, participants showed improved memory for information that they were curious about and for incidental material learned during states of high curiosity. Functional magnetic resonance imaging results revealed that activity in the midbrain and the nucleus accumbens was enhanced during states of high curiosity. Importantly, individual variability in curiosity-driven memory benefits for incidental material was supported by anticipatory activity in the midbrain and hippocampus and by functional connectivity between these regions. These findings suggest a link between the mechanisms supporting extrinsic reward motivation and intrinsic curiosity and highlight the importance of stimulating curiosity to create more effective learning experiences.
Read also: How the Power of Interest Drives Learning
Cognitive neuroscientists increasingly recognize that continued progress in understanding human brain function will require not only the acquisition of new data, but also the synthesis and integration of data across studies and laboratories. Here we review ongoing efforts to develop a more cumulative science of human brain function. We discuss the rationale for an increased focus on formal synthesis of the cognitive neuroscience literature, provide an overview of recently developed tools and platforms designed to facilitate the sharing and integration of neuroimaging data, and conclude with a discussion of several emerging developments that hold even greater promise in advancing the study of human brain function.
The explosive growth of human brain mapping over the past two decades has raised important challenges for the field. As the primary literature expands, the need for powerful tools capable of synthesizing and distilling the findings of many different studies grow commensurately. The present article highlighted the benefits of a synthesis oriented research strategy and reviewed several ongoing efforts to facilitate greater integration of the published literature. Going forward, such integration will undoubtedly accelerate progress in elucidating the neural mechanisms that support the full range of human thought, feeling, and action in health and disease. There is every reason to push forward energetically on efforts to develop a cumulative science of human brain function.
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.
One of the striking developments of modern times is an appreciation of how unbounded things are. Social networks have transformed our understanding of the nature of the individual. Phones allow another person to be present to us even when they are miles away, destroying the illusion of boundaries.
I travel and I can access my latest work documents, my deepest, most intimate thoughts on the cloud, so where are my most deepest, most significant thoughts? Where am I working? Where am I located? We ourselves are distributed dynamically, extended beings who are always becoming through our action. That is a very profound, new way of thinking about what we are. But sadly so often in the sciences of mind, this new way of thinking about ourselves is overlooked as a possibility. Too many cognitive scientists, not all, but the majority tend to take really a 17th century conception of the person as an individual island trapped inside his or her head. We need to break free of that.
Now, the only way to move forward is through an integrated, contextualized neuroscience of consciousness.
Cognitive neuroscience studies of creativity have appeared with increasing frequently in recent years. Yet to date, no comprehensive and critical review of these studies has yet been published. The ﬁrst part of this article presents a quick overview of the 3 primary methodologies used by cognitive neuroscientists: electroencephalography (EEG), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI). The second part provides a comprehensive review of cognitive neuroscience studies of creativity-related cognitive processes. The third part critically examines these studies; the goal is to be extremely clear about exactly what interpretations can appropriately be made of these studies. The conclusion provides recommendations for future research collaborations between creativity researchers and cognitive neuroscientists.
Many disciplines, including philosophy, history, and sociology, have attempted to make sense of how science works. In this book, Paul Thagard examines scientific development from the interdisciplinary perspective of cognitive science. Cognitive science combines insights from researchers in many fields: philosophers analyze historical cases, psychologists carry out behavioral experiments, neuro-scientists perform brain scans, and computer modelers write programs that simulate thought processes.
Thagard develops cognitive perspectives on the nature of explanation, mental models, theory choice, and resistance to scientific change, considering disbelief in climate change as a case study. He presents a series of studies that describe the psychological and neural processes that have led to breakthroughs in science, medicine, and technology. He shows how discoveries of new theories and explanations lead to conceptual change, with examples from biology, psychology, and medicine. Finally, he shows how the cognitive science of science can integrate descriptive and normative concerns; and he considers the neural underpinnings of certain scientific concepts.