Results 11 to 20 of about 169,052 (301)

Single-molecule analysis of intracellular insulin granule behavior and its application to analyzing cytoskeletal dependence and pathophysiological implications

Frontiers in Physiology, 2023
Introduction: Mobilization of intracellular insulin granules to the plasma membrane plays a crucial role in regulating insulin secretion. However, the regulatory mechanisms of this mobilization process have been poorly understood due to technical ...
Hiroyasu Hatakeyama, Tomomi Oshima, Shinichiro Ono, Yuichi Morimoto, Yuichi Morimoto, Noriko Takahashi   +5 more
doaj   +1 more source

Improved Separation of Odor Responses in Granule Cells of the Olfactory Bulb During Odor Discrimination Learning

Frontiers in Cellular Neuroscience, 2020
In the olfactory bulb, olfactory information is translated into ensemble representations by mitral/tufted cells, and these representations change dynamically in a context-dependent manner.
Dejuan Wang, Yang Chen, Yiling Chen, Xiaowen Li, Penglai Liu, Zhaoyang Yin, Anan Li   +6 more
doaj   +1 more source

Data granulation by the principles of uncertainty [PDF]

, 2015
Researches in granular modeling produced a variety of mathematical models, such as intervals, (higher-order) fuzzy sets, rough sets, and shadowed sets, which are all suitable to characterize the so-called information granules.
Livi, Lorenzo, Sadeghian, Alireza
core   +1 more source

Hybrid Learning for General Type-2 TSK Fuzzy Logic Systems

Algorithms, 2017
This work is focused on creating fuzzy granular classification models based on general type-2 fuzzy logic systems when consequents are represented by interval type-2 TSK linear functions. Due to the complexity of general type-2 TSK fuzzy logic systems, a
Mauricio A. Sanchez, Juan R. Castro, Violeta Ocegueda-Miramontes, Leticia Cervantes   +3 more
doaj   +1 more source

A Granular Computing Based Classification Method From Algebraic Granule Structure

IEEE Access, 2021
Classification, as one of the main task of machine learning, corresponds to the core work of granular computing, namely granulation. Most of granular computing models and related classification methods are uniquely classifying by granule features, but ...
Linshu Chen, Lei Zhao, Zhenguo Xiao, Yuanhui Liu, Jiayang Wang   +4 more
doaj   +1 more source

Insulin secretory granules labelled with phogrin-fluorescent proteins show alterations in size, mobility and responsiveness to glucose stimulation in living β-cells [PDF]

, 2019
The intracellular life of insulin secretory granules (ISGs) from biogenesis to secretion depends on their structural (e.g. size) and dynamic (e.g. diffusivity, mode of motion) properties.
Bugliani, Marco, Cappello, Valentina, Caracciolo, Giulio, Cardarelli, Francesco, Digiacomo, Luca, Ferri, Gianmarco, Lavagnino, Zeno, Marchetti, Piero, Occhipinti, Margherita, Piston, David W.   +9 more
core   +3 more sources

Uncertainty Measurement for a Grey Information System

IEEE Access, 2019
A grey information system (GIS) is a new kind of IS. Uncertainty measurement (UM) can provide a new perspective for data analysis and help to reveal the essential features of data. This article studies UM for a GIS.
Zhihong Wang, Zhaowen Li, Hongxiang Tang, Gangqiang Zhang, Ningxin Xie   +4 more
doaj   +1 more source

Reading out a spatiotemporal population code by imaging neighbouring parallel fibre axons in vivo. [PDF]

, 2015
The spatiotemporal pattern of synaptic inputs to the dendritic tree is crucial for synaptic integration and plasticity. However, it is not known if input patterns driven by sensory stimuli are structured or random.
Häusser, M, Wilms, CD
core   +1 more source

A Sparse, Spatially Biased Subtype of Mature Granule Cell Dominates Recruitment in Hippocampal-Associated Behaviors

Cell Reports, 2020
Summary: Animals can store information about experiences by activating specific neuronal populations, and subsequent reactivation of these neural ensembles can lead to recall of salient experiences.
Sarah R. Erwin, Weinan Sun, Monique Copeland, Sarah Lindo, Nelson Spruston, Mark S. Cembrowski   +5 more
doaj   +1 more source

Neurogenesis Drives Stimulus Decorrelation in a Model of the Olfactory Bulb [PDF]

, 2012
The reshaping and decorrelation of similar activity patterns by neuronal networks can enhance their discriminability, storage, and retrieval. How can such networks learn to decorrelate new complex patterns, as they arise in the olfactory system?
A Arevian, A Fantana, A Mouret, A Mouret, A Sahay, AM McNamara, B Johnson, B Winner, Boris S. Gutkin, C Linster, C Rochefort, CW Lin, D Chaudhury, D Rinberg, D Wilson, DA Wilson, DJ Heeger, E Yaksi, F David, F Kermen, F Lazarini, F Lazarini, GA Cecchi, GK Mak, GK Mak, GM Shepherd, Hermann Riecke, I Imayoshi, I Ortega-Perez, J Ninkovic, JT Davie, L Belnoue, L Petreanu, LM Kay, M Alonso, M Satou, M Valley, M Whitman, M Yamaguchi, MC Whitman, MD Döbrössy, MM Moreno, MT Wiechert, N Kaneko, N Mandairon, N Mandairon, N Mandairon, N Mandairon, N Mandairon, N Mandairon, N Miwa, O Escanilla, P Panzanelli, PA Brennan, PE Castillo, PM Lledo, Q Nai, R Pressler, RE Dolmetsch, RW Friedrich, RW Friedrich, S Sultan, S Sultan, S Sultan, S Wick, Siu-Fai Chow, SR Olsen, SS Magavi, Stuart D. Wick, SW Kuffler, SX Luo, T Shingo, TA Cleland, TA Cleland, TB Woolf, TK Yokoyama, V Breton-Provencher, V Egger, V Egger, W Kelsch, W Kim, Y Gao   +81 more
core   +6 more sources