We present a model of spatial navigation based on the non-convergent dynamics of brain activity. The system includes a hippocampal module that processes global spatial information and a cortical module that deals with local sensory information. We test the model using several spatial navigation paradigms: goal finding, shortcutting and detouring. Computer simulations show that the performance of the agent qualitatively matches that of animals and related models. This new approach provides a novel interpretation of how the brain accomplishes spatial navigation. 相似文献
We report the implementation of an electrostatic Einzel lens (Boersch) phase plate in a prototype transmission electron microscope dedicated to aberration-corrected cryo-EM. The combination of phase plate, Cs corrector and Diffraction Magnification Unit (DMU) as a new electron-optical element ensures minimal information loss due to obstruction by the phase plate and enables in-focus phase contrast imaging of large macromolecular assemblies. As no defocussing is necessary and the spherical aberration is corrected, maximal, non-oscillating phase contrast transfer can be achieved up to the information limit of the instrument. A microchip produced by a scalable micro-fabrication process has 10 phase plates, which are positioned in a conjugate, magnified diffraction plane generated by the DMU. Phase plates remained fully functional for weeks or months. The large distance between phase plate and the cryo sample permits the use of an effective anti-contaminator, resulting in ice contamination rates of <0.6 nm/h at the specimen. Maximal in-focus phase contrast was obtained by applying voltages between 80 and 700 mV to the phase plate electrode. The phase plate allows for in-focus imaging of biological objects with a signal-to-noise of 5-10 at a resolution of 2-3 nm, as demonstrated for frozen-hydrated virus particles and purple membrane at liquid-nitrogen temperature. 相似文献
In a paper recently published (ibid., vol.12, p. 30-8, 1993), Chiang and Sullivan compare a new criterion for image registration called CBC (coincident bit counting) with two criteria that the authors proposed some years ago, namely SSC and DSC (stochastic and deterministic sign change criteria). The authors' nonparametric approach was demonstrated to outperform the conventional image registration criteria for robust registration in the fact that the value of their similarity measure did not take the specific pixel values into account. In light of this observation, Chiang and Sullivan have built the CBC criterion. The CBC method compares the number of coincident bits between the corresponding pixels in two different frames for a fixed amount of displacement. While the authors consider that the CBC is of interest and deserves to be studied, they feel that the comparison made by Chiang and Sullivan was not entirely accurate. Here the authors comment on this comparison and suggest possible further studies. 相似文献
Discusses the evolution of the Psychological Review from its inception in 1894 as a general journal to its current status as a forum for theoretical discussion. A historical overview of Psychological Review is presented, and its 2 main subfields, cognition and perception, are outlined. (PsycINFO Database Record (c) 2010 APA, all rights reserved) 相似文献
We introduce a novel algorithm for online estimation of Acoustic Impulse Responses (AIRs) which allows for fast convergence by exploiting prior knowledge about the fundamental structure of AIRs. The proposed method assumes that the variability of AIRs of an acoustic scene is confined to a low-dimensional manifold which is embedded in a high-dimensional space of possible AIR estimates. We discuss various approaches which exploit a training data set of AIRs, e.g., high-accuracy AIR estimates from the acoustic scene, to learn a local affine subspace approximation of the AIR manifold. The model is motivated by the idea of describing the generally nonlinear AIR manifold locally by tangential hyperplanes and its validity is verified for simulated data. Subsequently, we describe how the manifold assumption can be used to enhance online AIR estimates by projecting them onto an adaptively estimated subspace. Motivated by the assumption of manifolds being locally Euclidean, the parameters determining the adaptive subspace are learned from the nearest neighbor AIR training samples to the current AIR estimate. To assess the proximity of training data AIRs to the current AIR estimate, we introduce a probabilistic extension of the Euclidean distance which improves the performance for applications with non-white excitation signals. Furthermore, we describe how model imperfections can be tackled by a soft projection of the AIR estimates. The proposed algorithm exhibits significantly faster convergence properties in comparison to a high-performance state-of-the-art algorithm. Furthermore, we show an improved steady-state performance for speech-excited system identification scenarios suffering from high-level interfering noise and nonunique solutions.