Search results for " Cognitive Neuroscience"

Plasticity of brain wave network interactions and evolution across physiologic states

2015

Neural plasticity transcends a range of spatio-temporal scales and serves as the basis of various brain activities and physiologic functions. At the microscopic level, it enables the emergence of brain waves with complex temporal dynamics. At the macroscopic level, presence and dominance of specific brain waves is associated with important brain functions. The role of neural plasticity at different levels in generating distinct brain rhythms and how brain rhythms communicate with each other across brain areas to generate physiologic states and functions remains not understood. Here we perform an empirical exploration of neural plasticity at the level of brain wave network interactions repre…

Optokinetic stimulation affects temporal estimation in healthy humans

2007

The representation of time and space are closely linked in the cognitive system. Optokinetic stimulation modulates spatial attention in healthy subjects and patients with spatial neglect. In order to evaluate whether optokinetic stimulation could influence time perception, a group of healthy subjects performed "time-comparison" tasks of sub- and supra-second intervals before and after leftward or rightward optokinetic stimulation. Subjective time perception was biased by the direction of optokinetic stimulation. Rightward optokinetic stimulation induced an overestimation of time perception compared with baseline and leftward optokinetic stimulation. These results indicate a directional bias…

A robust aerial image registration method using Gaussian mixture models

2014

Aerial image registration is one of the bases in many aerospace applications, such as aerial reconnaissance and aerial mapping. In this paper, we propose a novel aerial image registration algorithm which is based on Gaussian mixture models. First of all, considering the characters of the aerial images, the work uses a shape feature detector which computes the boundaries of regions with nearly the same gray-value to extract invariant feature. Then, a Gaussian mixture models (GMM) based image registration model is built and solved to estimate the transformation matrix between two aerial images. Furthermore, the proposed method is applied on real aerial images, and the results demonstrate the …

Haptoglobin interacts with apolipoprotein E and beta-amyloid and influences their crosstalk.

2014

Beta-amyloid accumulation in brain is a driving force for Alzheimer's disease pathogenesis. Apolipoprotein E (ApoE) represents a critical player in beta-amyloid homeostasis, but its role in disease progression is controversial. We previously reported that the acute-phase protein haptoglobin binds ApoE and impairs its function in cholesterol homeostasis. The major aims of this study were to characterize the binding of haptoglobin to beta-amyloid, and to evaluate whether haptoglobin affects ApoE binding to beta-amyloid. Haptoglobin is here reported to form a complex with beta-amyloid as shown by immunoblotting experiments with purified proteins, or by its immunoprecipitation in brain tissues …

A Systematic Nomenclature for the Insect Brain

2014

SummaryDespite the importance of the insect nervous system for functional and developmental neuroscience, descriptions of insect brains have suffered from a lack of uniform nomenclature. Ambiguous definitions of brain regions and fiber bundles have contributed to the variation of names used to describe the same structure. The lack of clearly determined neuropil boundaries has made it difficult to document precise locations of neuronal projections for connectomics study. To address such issues, a consortium of neurobiologists studying arthropod brains, the Insect Brain Name Working Group, has established the present hierarchical nomenclature system, using the brain of Drosophila melanogaster…

Neurocognitive Developmental Disorders: A Real Challenge for Developmental Neuropsychology

2002

Conceptual Spaces for Cognitive Architectures: A lingua franca for different levels of representation

2017

During the last decades, many cognitive architectures (CAs) have been realized adopting different assumptions about the organization and the representation of their knowledge level. Some of them (e.g. SOAR [Laird (2012)]) adopt a classical symbolic approach, some (e.g. LEABRA [O'Reilly and Munakata (2000)]) are based on a purely connectionist model, while others (e.g. CLARION [Sun (2006)] adopt a hybrid approach combining connectionist and symbolic representational levels. Additionally, some attempts (e.g. biSOAR) trying to extend the representational capacities of CAs by integrating diagrammatical representations and reasoning are also available [Kurup and Chandrasekaran (2007)]. In this p…

Finite-time boundedness for uncertain discrete neural networks with time-delays and Markovian jumps

2014

This paper is concerned with stochastic finite-time boundedness analysis for a class of uncertain discrete-time neural networks with Markovian jump parameters and time-delays. The concepts of stochastic finite-time stability and stochastic finite-time boundedness are first given for neural networks. Then, applying the Lyapunov approach and the linear matrix inequality technique, sufficient criteria on stochastic finite-time boundedness are provided for the class of nominal or uncertain discrete-time neural networks with Markovian jump parameters and time-delays. It is shown that the derived conditions are characterized in terms of the solution to these linear matrix inequalities. Finally, n…

Design of unknown inputs proportional integral observers for TS fuzzy models

2014

In this paper the design of unknown inputs proportional integral observers for Takagi-Sugeno (TS) fuzzy models subject to unmeasurable decision variables is proposed. These unknown inputs affect both state and output of the system. The synthesis of these observers is based on two hypotheses that the unknown inputs are under the polynomials form with their kth derivatives zero for the first one and bounded norm for the second one, hence two approaches. The Lyapunov theory and L"2-gain technique are used to develop the stability conditions of such observers in LMIs (linear matrix inequality) formulation. A simulation example is given to validate and compare the proposed design conditions for …

Impaired semantic processing during sentence reading in children with dyslexia: combined fMRI and ERP evidence

2008

Developmental dyslexia is a specific disorder of reading acquisition characterized by a phonological core deficit. Sentence reading is also impaired in dyslexic readers, but whether semantic processing deficits contribute is unclear. Combining spatially and temporally sensitive neuroimaging techniques to focus on semantic processing can provide a more comprehensive characterization of sentence reading in dyslexia. We recorded brain activity from 52 children (16 with dyslexia, 31 controls) with functional magnetic resonance imaging (fMRI) and event-related potentials (ERP) in two separate counterbalanced sessions. The children silently read and occasionally judged simple sentences with seman…