The discharge patterns of neurons in auditory centers encode information about sounds.However,few studies have focused on the synaptic mechanisms underlying the shaping of discharge patterns using intracellular record...The discharge patterns of neurons in auditory centers encode information about sounds.However,few studies have focused on the synaptic mechanisms underlying the shaping of discharge patterns using intracellular recording techniques.Here,we investigated the discharge patterns of inferior collicular（IC）neurons using intracellular recordings to further elucidate the mechanisms underlying the shaping of discharge patterns.Under in vivo intracellular recording conditions,recordings were obtained from 66 IC neurons in 18 healthy adult mice（Mus musculus,Km）under free field-stimulation.Fiftyeight of these neurons fired bursts of action potentials（APs）to auditory stimuli and the remaining eight just generated local responses such as excitatory（n=4）or inhibitory（n=4）postsynaptic potentials.Based on the APs and subthreshold responses,the discharge patterns were classified into seven types：phasic（24/58,41.4%）,phasic burst（8/58,13.8%）,pauser（4/58,6.9%）,phasic-pauser（1/58,1.7%）,chopper（2/58,3.4%）,primary-like tonic（14/58,24.1%）and sound-induced inhibitory（5/58,8.6%）.We concluded that（1）IC neurons exhibit at least seven distinct discharge patterns;（2）inhibition participates in shaping the discharge pattern of most IC neurons and plays a role in sculpting the pattern,except for the primary-like tonic pattern which was not shapedby inhibition;and（3）local neural circuits are the likely structural basis that shapes the discharge patterns of IC neurons and can be formed either in the IC or in lower-level auditory structures.展开更多
The latest developments in bio-inspired neuromorphic vision sensors can be summarized in 3 keywords:smaller,faster,and smarter.(1)Smaller:Devices are becoming more compact by integrating previously separated component...The latest developments in bio-inspired neuromorphic vision sensors can be summarized in 3 keywords:smaller,faster,and smarter.(1)Smaller:Devices are becoming more compact by integrating previously separated components such as sensors,memory,and processing units.As a prime example,the transition from traditional sensory vision computing to in-sensor vision computing has shown clear benefits,such as simpler circuitry,lower power consumption,and less data redundancy.(2)Swifter:Owing to the nature of physics,smaller and more integrated devices can detect,process,and react to input more quickly.In addition,the methods for sensing and processing optical information using various materials(such as oxide semiconductors)are evolving.(3)Smarter:Owing to these two main research directions,we can expect advanced applications such as adaptive vision sensors,collision sensors,and nociceptive sensors.This review mainly focuses on the recent progress,working mechanisms,image pre-processing techniques,and advanced features of two types of neuromorphic vision sensors based on near-sensor and in-sensor vision computing methodologies.展开更多
Memristor with memory properties can be applied to connection points(synapses)between cells in a cellular neural network(CNN).This paper highlights memristor crossbar-based multilayer CNN(MCM-CNN)and its application t...Memristor with memory properties can be applied to connection points(synapses)between cells in a cellular neural network(CNN).This paper highlights memristor crossbar-based multilayer CNN(MCM-CNN)and its application to edge detection.An MCM-CNN is designed by adopting a memristor crossbar composed of a pair of memristors.MCM-CNN based on the memristor crossbar with changeable weight is suitable for edge detection of a binary image and a color image considering its characteristics of programmablization and compactation.Figure of merit(FOM)is introduced to evaluate the proposed structure and several traditional edge detection operators for edge detection results.Experiment results show that the FOM of MCM-CNN is three times more than that of the traditional edge detection operators.展开更多
基金supported by grants from the National Natural Science Foundation of China (31070971,31000959)
文摘The discharge patterns of neurons in auditory centers encode information about sounds.However,few studies have focused on the synaptic mechanisms underlying the shaping of discharge patterns using intracellular recording techniques.Here,we investigated the discharge patterns of inferior collicular（IC）neurons using intracellular recordings to further elucidate the mechanisms underlying the shaping of discharge patterns.Under in vivo intracellular recording conditions,recordings were obtained from 66 IC neurons in 18 healthy adult mice（Mus musculus,Km）under free field-stimulation.Fiftyeight of these neurons fired bursts of action potentials（APs）to auditory stimuli and the remaining eight just generated local responses such as excitatory（n=4）or inhibitory（n=4）postsynaptic potentials.Based on the APs and subthreshold responses,the discharge patterns were classified into seven types：phasic（24/58,41.4%）,phasic burst（8/58,13.8%）,pauser（4/58,6.9%）,phasic-pauser（1/58,1.7%）,chopper（2/58,3.4%）,primary-like tonic（14/58,24.1%）and sound-induced inhibitory（5/58,8.6%）.We concluded that（1）IC neurons exhibit at least seven distinct discharge patterns;（2）inhibition participates in shaping the discharge pattern of most IC neurons and plays a role in sculpting the pattern,except for the primary-like tonic pattern which was not shapedby inhibition;and（3）local neural circuits are the likely structural basis that shapes the discharge patterns of IC neurons and can be formed either in the IC or in lower-level auditory structures.
基金This work was supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.NRF-2019R1A2C2002447)This research also was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(No.NRF-2014R1A6A1030419)This work also was supported by Korea Institute for Advancement of Technology(KIAT)grant funded by the Korea Government(MOTIE)(P0020967,Advanced Training Program for Smart Sensor Engineers).
文摘The latest developments in bio-inspired neuromorphic vision sensors can be summarized in 3 keywords:smaller,faster,and smarter.(1)Smaller:Devices are becoming more compact by integrating previously separated components such as sensors,memory,and processing units.As a prime example,the transition from traditional sensory vision computing to in-sensor vision computing has shown clear benefits,such as simpler circuitry,lower power consumption,and less data redundancy.(2)Swifter:Owing to the nature of physics,smaller and more integrated devices can detect,process,and react to input more quickly.In addition,the methods for sensing and processing optical information using various materials(such as oxide semiconductors)are evolving.(3)Smarter:Owing to these two main research directions,we can expect advanced applications such as adaptive vision sensors,collision sensors,and nociceptive sensors.This review mainly focuses on the recent progress,working mechanisms,image pre-processing techniques,and advanced features of two types of neuromorphic vision sensors based on near-sensor and in-sensor vision computing methodologies.
基金supported by the Research Fund for International Young Scientists of the National Natural Science Foundation of China(61550110248)the Research on Fundamental Theory of Shared Intelligent Street Lamp for New Scene Service(H04W200495)+1 种基金Sichuan Science and Technology Program(2019YFG0190)the Research on Sino-Tibetan Multi-source Information Acquisition,Fusion,Data Mining and its Application(H04W170186).
文摘Memristor with memory properties can be applied to connection points(synapses)between cells in a cellular neural network(CNN).This paper highlights memristor crossbar-based multilayer CNN(MCM-CNN)and its application to edge detection.An MCM-CNN is designed by adopting a memristor crossbar composed of a pair of memristors.MCM-CNN based on the memristor crossbar with changeable weight is suitable for edge detection of a binary image and a color image considering its characteristics of programmablization and compactation.Figure of merit(FOM)is introduced to evaluate the proposed structure and several traditional edge detection operators for edge detection results.Experiment results show that the FOM of MCM-CNN is three times more than that of the traditional edge detection operators.
