70,551 research outputs found
Order and disorder in everyday action: the roles of contention scheduling and supervisory attention
This paper describes the contention scheduling/supervisory attentional system approach to action selection and uses this account to structure a survey of current theories of the control of action. The focus is on how such theories account for the types of error produced by some patients with frontal and/or left temporoparietal damage when attempting everyday tasks. Four issues, concerning both the theories and their accounts of everyday action breakdown, emerge: first, whether multiple control systems, each capable of controlling action in different situations, exist; second, whether different forms of damage at the neural level result in conceptually distinct disorders; third, whether semantic/conceptual knowledge of objects and actions can be dissociated from control mechanisms, and if so what computational principles govern sequential control; and fourth, whether disorders of everyday action should be attributed to a loss of semantic/conceptual knowledge, a malfunction of control, or some combination of the two
Adaptive Guidance: Enhancing Self-Regulation, Knowledge, and Performance in Technology-Based Training
Considerable research has examined the effects of giving trainees control over their learning (Steinberg, 1977, 1989; Williams, 1993). The most consistent finding of this research has been that trainees do not make good instructional use of the control they are given. Yet, today’s technologically based training systems often provide individuals with significant control over their learning (Brown, 2001). This creates a dilemma that must be addressed if technology is going to be used to create more effective training systems. The current study extended past research that has examined the effects of providing trainees with some form of advisement or guidance in addition to learner control and examined the impact of an instructional strategy, adaptive guidance, on learning and performance in a complex training environment. Overall, it was found that adaptive guidance had a substantial effect on the nature of trainees’ study and practice, self-regulation, knowledge acquired, and performance
Quantitative Comparison of Abundance Structures of Generalized Communities: From B-Cell Receptor Repertoires to Microbiomes
The \emph{community}, the assemblage of organisms co-existing in a given
space and time, has the potential to become one of the unifying concepts of
biology, especially with the advent of high-throughput sequencing experiments
that reveal genetic diversity exhaustively. In this spirit we show that a tool
from community ecology, the Rank Abundance Distribution (RAD), can be turned by
the new MaxRank normalization method into a generic, expressive descriptor for
quantitative comparison of communities in many areas of biology. To illustrate
the versatility of the method, we analyze RADs from various \emph{generalized
communities}, i.e.\ assemblages of genetically diverse cells or organisms,
including human B cells, gut microbiomes under antibiotic treatment and of
different ages and countries of origin, and other human and environmental
microbial communities. We show that normalized RADs enable novel quantitative
approaches that help to understand structures and dynamics of complex
generalize communities
Genomics clarifies taxonomic boundaries in a difficult species complex.
Efforts to taxonomically delineate species are often confounded with conflicting information and subjective interpretation. Advances in genomic methods have resulted in a new approach to taxonomic identification that stands to greatly reduce much of this conflict. This approach is ideal for species complexes, where divergence times are recent (evolutionarily) and lineages less well defined. The California Roach/Hitch fish species complex is an excellent example, experiencing a convoluted geologic history, diverse habitats, conflicting species designations and potential admixture between species. Here we use this fish complex to illustrate how genomics can be used to better clarify and assign taxonomic categories. We performed restriction-site associated DNA (RAD) sequencing on 255 Roach and Hitch samples collected throughout California to discover and genotype thousands of single nucleotide polymorphism (SNPs). Data were then used in hierarchical principal component, admixture, and FST analyses to provide results that consistently resolved a number of ambiguities and provided novel insights across a range of taxonomic levels. At the highest level, our results show that the CA Roach/Hitch complex should be considered five species split into two genera (4 + 1) as opposed to two species from distinct genera (1 +1). Subsequent levels revealed multiple subspecies and distinct population segments within identified species. At the lowest level, our results indicate Roach from a large coastal river are not native but instead introduced from a nearby river. Overall, this study provides a clear demonstration of the power of genomic methods for informing taxonomy and serves as a model for future studies wishing to decipher difficult species questions. By allowing for systematic identification across multiple scales, taxonomic structure can then be tied to historical and contemporary ecological, geographic or anthropogenic factors
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
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