scholarly journals Encoding model for continuous motion-sensitive neurons in the intermediate and deep layers of pigeon Optic Tectum

2021 ◽  
Author(s):  
Songwei Wang ◽  
Mengyu Zhao ◽  
Longlong Qian ◽  
Zhizhong Wang ◽  
Li Shi
Keyword(s):  
Optic Tectum ◽  
Detection Algorithm ◽  
Random Motion ◽  
Activation Mechanism ◽  
Small Target ◽  
Moving Targets ◽  
Continuous Motion ◽  
Information Encoding ◽  
Deep Layers

AbstractThere are typical neurons in the intermediate and deep layers of the optic tectum of avian, which are sensitive to small continuous moving targets. Based on this sensitivity of these neurons to continuous moving targets, the hypothesis of directed energy accumulation in dendrite field of these neurons is proposed. Based on the phenomenon that single dendrite activation can induce somatic spikes in vitro, the hypothesis of sequential probability activation mechanism of soma is proposed. Combined with the above hypotheses, the information encoding model of these typical neurons is constructed. Moreover, electrophysiological experiments and model simulations are carried out to obtain the response of neurons to visual stimuli of sequential motion, random motion and random sequential motion. Results show that the encoding model fits the response properties of continuous motion-sensitive neurons well. This study is of great significance for understanding the neurophysiological process of small-target perception for avian tectofugal pathway and the construction of the brain-inspired small-target detection algorithm.

scholarly journals Encoding model for continuous motion-sensitive neurons in the intermediate and deep layers of the pigeon optic tectum

Neuroscience ◽  
2022 ◽  
Author(s):  
Songwei Wang ◽  
Quangong Ma ◽  
Longlong Qian ◽  
Mengyu Zhao ◽  
Zhizhong Wang ◽  
...  
Keyword(s):  
Optic Tectum ◽  
Continuous Motion ◽  
Deep Layers

Infrared dim small target detection algorithm based on NSCT and SVD

2015 ◽  
Author(s):  
Ying Zhao ◽  
Gang Liu ◽  
Huixin Zhou ◽  
Hanlin Qin ◽  
Xiao Li ◽  
...  
Keyword(s):  
Target Detection ◽  
Detection Algorithm ◽  
Small Target ◽  
Small Target Detection

scholarly journals Cofactor bypass variants reveal a conformational control mechanism governing cell wall polymerase activity

2016 ◽  
Vol 113 (17) ◽  
pp. 4788-4793 ◽  
Author(s):  
Monica Markovski ◽  
Jessica L. Bohrhunter ◽  
Tania J. Lupoli ◽  
Tsuyoshi Uehara ◽  
Suzanne Walker ◽  
...  
Keyword(s):  
Polymerase Activity ◽  
Activation Mechanism ◽  
Phenotypic Analysis ◽  
Outer Membranes ◽  
Division Site ◽  
Physiological Relevance ◽  
Membrane Lipoproteins ◽  
Shed Light

To fortify their cytoplasmic membrane and protect it from osmotic rupture, most bacteria surround themselves with a peptidoglycan (PG) exoskeleton synthesized by the penicillin-binding proteins (PBPs). As their name implies, these proteins are the targets of penicillin and related antibiotics. We and others have shown that the PG synthases PBP1b and PBP1a ofEscherichia colirequire the outer membrane lipoproteins LpoA and LpoB, respectively, for their in vivo function. Although it has been demonstrated that LpoB activates the PG polymerization activity of PBP1b in vitro, the mechanism of activation and its physiological relevance have remained unclear. We therefore selected for variants of PBP1b (PBP1b*) that bypass the LpoB requirement for in vivo function, reasoning that they would shed light on LpoB function and its activation mechanism. Several of these PBP1b variants were isolated and displayed elevated polymerization activity in vitro, indicating that the activation of glycan polymer growth is indeed one of the relevant functions of LpoB in vivo. Moreover, the location of amino acid substitutions causing the bypass phenotype on the PBP1b structure support a model in which polymerization activation proceeds via the induction of a conformational change in PBP1b initiated by LpoB binding to its UB2H domain, followed by its transmission to the glycosyl transferase active site. Finally, phenotypic analysis of strains carrying a PBP1b* variant revealed that the PBP1b–LpoB complex is most likely not providing an important physical link between the inner and outer membranes at the division site, as has been previously proposed.

scholarly journals An axon initial segment is required for temporal precision in action potential encoding by neuronal populations

2018 ◽  
Vol 4 (11) ◽  
pp. eaau8621 ◽  
Author(s):  
Elinor Lazarov ◽  
Melanie Dannemeyer ◽  
Barbara Feulner ◽  
Jörg Enderlein ◽  
Michael J. Gutnick ◽  
...  
Keyword(s):  
Initial Segment ◽  
Axon Initial Segment ◽  
High Concentration ◽  
Information Encoding ◽  
Temporal Precision ◽  
Network Function ◽  
Evolutionary Innovation ◽  
Voltage Dependent ◽  
Vitro Model

Central neurons initiate action potentials (APs) in the axon initial segment (AIS), a compartment characterized by a high concentration of voltage-dependent ion channels and specialized cytoskeletal anchoring proteins arranged in a regular nanoscale pattern. Although the AIS was a key evolutionary innovation in neurons, the functional benefits it confers are not clear. Using a mutation of the AIS cytoskeletal protein βIV-spectrin, we here establish an in vitro model of neurons with a perturbed AIS architecture that retains nanoscale order but loses the ability to maintain a high NaV density. Combining experiments and simulations, we show that a high NaV density in the AIS is not required for axonal AP initiation; it is, however, crucial for a high bandwidth of information encoding and AP timing precision. Our results provide the first experimental demonstration of axonal AP initiation without high axonal channel density and suggest that increasing the bandwidth of the neuronal code and, hence, the computational efficiency of network function, was a major benefit of the evolution of the AIS.

Small Target Real-Time Detection Algorithm Based on Improved MDSSD

2020 ◽  
Vol 57 (20) ◽  
pp. 201009
Author(s):  
奚琦 Xi Qi ◽  
张正道 Zhang Zhengdao ◽  
彭力 Peng Li
Keyword(s):  
Real Time ◽  
Detection Algorithm ◽  
Small Target ◽  
Real Time Detection
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