scholarly journals Individuation of objects and object parts rely on the same neuronal mechanism

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Marlene Poncet ◽  
Alfonso Caramazza ◽  
Veronica Mazza
Keyword(s):  
Neuronal Mechanism ◽  
Object Parts

Non-neuronal regulation and repertoire of cholinergic receptors in organs

2010 ◽  
Vol 1 (5-6) ◽  
pp. 357-366
Author(s):  
Tsuyoshi Sato ◽  
Dai Chida ◽  
Takanori Iwata ◽  
Michihiko Usui ◽  
Kouki Hatori ◽  
...  
Keyword(s):  
Therapeutic Agents ◽  
Cholinergic Receptors ◽  
Target Cells ◽  
Neuronal Mechanism ◽  
Neuronal Regulation ◽  
Cholinergic Pathway

AbstractMany studies on the cholinergic pathway have indicated that cholinergic receptors, which are widely expressed in various cells, play an important role in all body organs. In this review, we present the concept that cholinergic responses are regulated through a neuronal or non-neuronal mechanism. The neuronal mechanism is a system in which acetylcholine binds to cholinergic receptors on target cells through the nerves. In the non-neuronal mechanism, acetylcholine, produced by neighboring cells in an autocrine/paracrine manner, binds to cholinergic receptors on target cells. Both mechanisms subsequently lead to physiological and pathophysiological responses. We also investigated the subunits/subtypes of cholinergic receptors on target cells, physiological and pathophysiological responses of the organs via cholinergic receptors, and extracellular factors that alter the subtypes/subunits of cholinergic receptors. Collectively, this concept will elucidate how cholinergic responses occur and will help us conduct further experiments to develop new therapeutic agents.

scholarly journals Neuronal mechanism of nociceptin-induced modulation of learning and memory: Involvement of N-methyl-D-aspartate receptors

2003 ◽  
Vol 8 (8) ◽  
pp. 752-765 ◽  
Author(s):  
T Mamiya ◽  
K Yamada ◽  
Y Miyamoto ◽  
N König ◽  
Y Watanabe ◽  
...  
Keyword(s):  
Learning And Memory ◽  
Neuronal Mechanism

scholarly journals A release from crowding using task-irrelevant object parts

2013 ◽  
Vol 13 (9) ◽  
pp. 622-622
Author(s):  
J. Greenwood ◽  
P. Cavanagh
Keyword(s):  
Object Parts ◽  
Task Irrelevant

Bayesian Networks for Image Understanding

2007 ◽  
pp. 128-150
Author(s):  
Andreas Savaki ◽  
Jiebo Luo ◽  
Michael Kane
Keyword(s):  
Bayesian Networks ◽  
Object Detection ◽  
Bayesian Network ◽  
Structure Learning ◽  
Image Understanding ◽  
Semantic Features ◽  
Scene Classification ◽  
Low Level ◽  
Object Parts ◽  
Scene Content

Image understanding deals with extracting and interpreting scene content for use in various applications. In this chapter, we illustrate that Bayesian networks are particularly well-suited for image understanding problems, and present case studies in indoor-outdoor scene classification and parts-based object detection. First, improved scene classification is accomplished using both low-level features, such as color and texture, and semantic features, such as the presence of sky and grass. Integration of low-level and semantic features is achieved using a Bayesian network framework. The network structure can be determined by expert opinion or by automated structure learning methods. Second, object detection at multiple views relies on a parts-based approach, where specialized detectors locate object parts and a Bayesian network acts as the arbitrator in order to determine the object presence. In general, Bayesian networks are found to be powerful integrators of different features and help improve the performance of image understanding systems.

scholarly journals Neuronal mechanism for acute mechanosensitivity in tactile-foraging waterfowl

2014 ◽  
Vol 111 (41) ◽  
pp. 14941-14946 ◽  
Author(s):  
E. R. Schneider ◽  
M. Mastrotto ◽  
W. J. Laursen ◽  
V. P. Schulz ◽  
J. B. Goodman ◽  
...  
Keyword(s):  
Neuronal Mechanism
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