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1.
Nat Neurosci ; 16(3): 264-6, 2013 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-23396101

RESUMO

Using Ca(2+) imaging in freely behaving mice that repeatedly explored a familiar environment, we tracked thousands of CA1 pyramidal cells' place fields over weeks. Place coding was dynamic, as each day the ensemble representation of this environment involved a unique subset of cells. However, cells in the ∼15-25% overlap between any two of these subsets retained the same place fields, which sufficed to preserve an accurate spatial representation across weeks.


Assuntos
Potenciais de Ação/fisiologia , Região CA1 Hipocampal/fisiologia , Cálcio/metabolismo , Células Piramidais/fisiologia , Animais , Meio Ambiente , Memória/fisiologia , Camundongos
2.
IEEE Trans Image Process ; 14(8): 1074-87, 2005 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-16121456

RESUMO

Recent advances in imaging sensor technology make high frame-rate video capture practical. As demonstrated in previous work, this capability can be used to enhance the performance of many image and video processing applications. The idea is to use the high frame-rate capability to temporally oversample the scene and, thus, to obtain more accurate information about scene motion and illumination. This information is then used to improve the performance of image and standard frame-rate video applications. This paper investigates the use of temporal oversampling to improve the accuracy of optical flow estimation (OFE). A method for obtaining high accuracy optical flow estimates at a conventional standard frame rate, e.g., 30 frames/s, by first capturing and processing a high frame-rate version of the video is presented. The method uses the Lucas-Kanade algorithm to obtain optical flow estimates at a high frame rate, which are then accumulated and refined to estimate the optical flow at the desired standard frame rate. The method demonstrates significant improvements in OFE accuracy both on synthetically generated video sequences and on a real video sequence captured using an experimental high-speed imaging system. It is then shown that a key benefit of using temporal oversampling to estimate optical flow is the reduction in motion aliasing. Using sinusoidal input sequences, the reduction in motion aliasing is identified and the desired minimum sampling rate as a function of the velocity and spatial bandwidth of the scene is determined. Using both synthetic and real video sequences, it is shown that temporal oversampling improves OFE accuracy by reducing motion aliasing not only for areas with large displacements but also for areas with small displacements and high spatial frequencies. The use of other OFE algorithms with temporally oversampled video is then discussed. In particular, the Haussecker algorithm is extended to work with high frame-rate sequences. This extension demonstrates yet another important benefit of temporal oversampling, which is improving OFE accuracy when brightness varies with time.


Assuntos
Algoritmos , Interpretação de Imagem Assistida por Computador/métodos , Imageamento Tridimensional/métodos , Armazenamento e Recuperação da Informação/métodos , Movimento , Reconhecimento Automatizado de Padrão/métodos , Processamento de Sinais Assistido por Computador , Gravação em Vídeo/métodos , Simulação por Computador , Aumento da Imagem/métodos , Modelos Estatísticos , Tamanho da Amostra
3.
Biosens Bioelectron ; 19(11): 1377-86, 2004 Jun 15.
Artigo em Inglês | MEDLINE | ID: mdl-15093208

RESUMO

Motivated by the design of an integrated CMOS-based detection platform, a simulation model for CCD and CMOS imager-based luminescence detection systems is developed. The model comprises four parts. The first portion models the process of photon flux generation from luminescence probes using ATP-based and luciferase label-based assay kinetics. An optics simulator is then used to compute the incident photon flux on the imaging plane for a given photon flux and system geometry. Subsequently, the output image is computed using a detailed imaging sensor model that accounts for photodetector spectral response, dark current, conversion gain, and various noise sources. Finally, signal processing algorithms are applied to the image to enhance detection reliability and hence increase the overall system throughput. To validate the model, simulation results are compared to experimental results obtained from a CCD-based system that was built to emulate the integrated CMOS-based platform.


Assuntos
Simulação por Computador , Medições Luminescentes , Modelos Teóricos , Algoritmos , Fatores de Tempo
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