101,750 research outputs found
New Ideas for Brain Modelling
This paper describes some biologically-inspired processes that could be used
to build the sort of networks that we associate with the human brain. New to
this paper, a 'refined' neuron will be proposed. This is a group of neurons
that by joining together can produce a more analogue system, but with the same
level of control and reliability that a binary neuron would have. With this new
structure, it will be possible to think of an essentially binary system in
terms of a more variable set of values. The paper also shows how recent
research associated with the new model, can be combined with established
theories, to produce a more complete picture. The propositions are largely in
line with conventional thinking, but possibly with one or two more radical
suggestions. An earlier cognitive model can be filled in with more specific
details, based on the new research results, where the components appear to fit
together almost seamlessly. The intention of the research has been to describe
plausible 'mechanical' processes that can produce the appropriate brain
structures and mechanisms, but that could be used without the magical
'intelligence' part that is still not fully understood. There are also some
important updates from an earlier version of this paper
Statistical thinking: From Tukey to Vardi and beyond
Data miners (minors?) and neural networkers tend to eschew modelling, misled
perhaps by misinterpretation of strongly expressed views of John Tukey. I
discuss Vardi's views of these issues as well as other aspects of Vardi's work
in emision tomography and in sampling bias.Comment: Published at http://dx.doi.org/10.1214/074921707000000210 in the IMS
Lecture Notes Monograph Series
(http://www.imstat.org/publications/lecnotes.htm) by the Institute of
Mathematical Statistics (http://www.imstat.org
Food Bioactives: Impact on Brain and Cardiometabolic Health â Findings from In Vitro to Human Studies
The search for dietary patterns or food bioactive derivatives that may serve as a panacea for health issues has been a topic of interest for several millennia. It is not surprising that this trend in food research is continuing today particularly in relation to brain and cardiometabolic health, given the huge burden they pose on human health, with no geographical boundaries. Currently, there is an increasing demand for âpureâ and âcleanâ foods as well as potent bioactive ingredients that can promote beneficial health outcomes. Several studies, including in vitro investigations, clinical trials, and observational studies related to food and nutritional patterns have already identified, proposed, and in some cases challenged the mechanisms of action of these foods and food ingredients. The book âFood bioactives and impact on brain and cardiometabolic health findings from in vitro to human studiesâ has gathered innovative, high-quality research manuscripts (letters to the editor, original research and review papers) on bioactive constituents of foods and dietary patterns which can directly impact upon brain and cardiometabolic health. These manuscripts reporting on different areas of this research field, from the description of new conceptual ideas, mechanisms of action, and structural modelling to clinical trials and observational studies
Investigation of sequence processing: A cognitive and computational neuroscience perspective
Serial order processing or sequence processing underlies
many human activities such as speech, language, skill
learning, planning, problem-solving, etc. Investigating
the neural bases of sequence processing enables us to
understand serial order in cognition and also helps in
building intelligent devices. In this article, we review
various cognitive issues related to sequence processing
with examples. Experimental results that give evidence
for the involvement of various brain areas will be described.
Finally, a theoretical approach based on statistical
models and reinforcement learning paradigm is
presented. These theoretical ideas are useful for studying
sequence learning in a principled way. This article
also suggests a two-way process diagram integrating
experimentation (cognitive neuroscience) and theory/
computational modelling (computational neuroscience).
This integrated framework is useful not only in the present
study of serial order, but also for understanding
many cognitive processes
Educational innovation, learning technologies and Virtual culture potentialâ
Learning technologies are regularly associated with innovative teaching but will they contribute to profound innovations in education itself? This paper addresses the question by building upon Merlin Donald's coâevolutionary theory of mind, cognition and culture. He claimed that the invention of technologies for storing and sharing external symbol systems, such as writing, gave rise to a âtheoretic cultureâ with rich symbolic representations and a resultant need for formal education. More recently, Shaffer and Kaput have claimed that the development of external and shared symbolâprocessing technologies is giving rise to an emerging âvirtual cultureâ. They argue that mathematics curricula are grounded in theoretic culture and should change to meet the novel demands of âvirtual cultureâ for symbolâprocessing and representational fluency. The generic character of their cultural claim is noted in this paper and it is suggested that equivalent pedagogic arguments are applicable across the educational spectrum. Hence, four general characteristics of virtual culture are proposed, against which applications of learning technologies can be evaluated for their innovative potential. Two illustrative uses of learning technologies are evaluated in terms of their âvirtual culture potentialâ and some anticipated questions about this approach are discussed towards the end of the paper
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