Memtransistors in which the source-drain channel conductance can be nonvolatilely manipulated through the gate signals have emerged as promising components for implementing neuromorphic computing.On the other side,it ...Memtransistors in which the source-drain channel conductance can be nonvolatilely manipulated through the gate signals have emerged as promising components for implementing neuromorphic computing.On the other side,it is known that the complementary metal-oxide-semiconductor(CMOS)field effect transistors have played the fundamental role in the modern integrated circuit technology.Therefore,will complementary memtransistors(CMT)also play such a role in the future neuromorphic circuits and chips?In this review,various types of materials and physical mechanisms for constructing CMT(how)are inspected with their merits and need-to-address challenges discussed.Then the unique properties(what)and poten-tial applications of CMT in different learning algorithms/scenarios of spiking neural networks(why)are reviewed,including super-vised rule,reinforcement one,dynamic vision with in-sensor computing,etc.Through exploiting the complementary structure-related novel functions,significant reduction of hardware consuming,enhancement of energy/efficiency ratio and other advan-tages have been gained,illustrating the alluring prospect of design technology co-optimization(DTCO)of CMT towards neuro-morphic computing.展开更多
Classic paired associative stimulation can improve synaptic plasticity,as demonstrated by animal expe riments and human clinical trials in spinal cord injury patients.Paired associative magnetic stimulation(dual-targe...Classic paired associative stimulation can improve synaptic plasticity,as demonstrated by animal expe riments and human clinical trials in spinal cord injury patients.Paired associative magnetic stimulation(dual-target peripheral and central magnetic stimulation)has been shown to promote neurologic recove ry after stroke.However,it remains unclear whether paired associative magnetic stimulation can promote recovery of lower limb motor dysfunction after spinal cord injury.We hypothesize that the curre nt caused by central and peripheral magnetic stimulation will conve rge at the synapse,which will promote synapse function and improve the motor function of the relevant muscles.Therefore,this study aimed to examine the effects of paired associative magnetic stimulation on neural circuit activation by measuring changes in motor evoked and somatosensory evoked potentials,motor and sensory function of the lower limbs,functional health and activities of daily living,and depression in patients with spinal co rd injury.We will recruit 110 thora cic spinal trauma patients treated in the Department of Spinal Cord Injury,China Rehabilitation Hospital and randomly assign them to expe rimental and control groups in a 1:1 ratio.The trial group(n=55)will be treated with paired associative magnetic stimulation and conventional rehabilitation treatment.The control group(n=55)will be treated with sham stimulation and co nventional rehabilitation treatment.Outcomes will be measured at four time points:baseline and 4,12,and 24 wee ks after the start of inte rvention(active or sham paired associative magnetic stimulation).The primary outcome measure of this trial is change in lower limb American Spinal Injury Association Impairment Scale motor function score from baseline to last follow-up.Secondary outcome measures include changes in lower limb American Spinal Injury Association sensory function sco re,motor evoked potentials,sensory evoked potentials,modified Ashwo rth scale score,Maslach Burnout Invento ry score,and Hamilton Depres展开更多
Current-induced multilevel magnetization switching in ferrimagnetic spintronic devices is highly pursued for the application in neuromorphic computing.In this work,we demonstrate the switching plasticity in Co/Gd ferr...Current-induced multilevel magnetization switching in ferrimagnetic spintronic devices is highly pursued for the application in neuromorphic computing.In this work,we demonstrate the switching plasticity in Co/Gd ferrimagnetic multilayers where the binary states magnetization switching induced by spin–orbit toque can be tuned into a multistate one as decreasing the domain nucleation barrier.Therefore,the switching plasticity can be tuned by the perpendicular magnetic anisotropy of the multilayers and the in-plane magnetic field.Moreover,we used the switching plasticity of Co/Gd multilayers for demonstrating spike timing-dependent plasticity and sigmoid-like activation behavior.This work gives useful guidance to design multilevel spintronic devices which could be applied in high-performance neuromorphic computing.展开更多
Phase transitions widely exist in nature and occur when some control parameters are changed. In neural systems, their macroscopic states are represented by the activity states of neuron populations, and phase transiti...Phase transitions widely exist in nature and occur when some control parameters are changed. In neural systems, their macroscopic states are represented by the activity states of neuron populations, and phase transitions between different activity states are closely related to corresponding functions in the brain. In particular, phase transitions to some rhythmic synchronous firing states play significant roles on diverse brain functions and disfunctions, such as encoding rhythmical external stimuli, epileptic seizure, etc. However, in previous studies, phase transitions in neuronal networks are almost driven by network parameters （e.g., external stimuli）, and there has been no investigation about the transitions between typical activity states of neuronal networks in a self-organized way by applying plastic connection weights. In this paper, we discuss phase transitions in electrically coupled and lattice-based small-world neuronal networks （LBSW networks） under spike-timing-dependent plasticity （STDP）. By applying STDP on all electrical synapses, various known and novel phase transitions could emerge in LBSW networks, particularly, the phenomenon of self-organized phase transitions （SOPTs）： repeated transitions between synchronous and asynchronous firing states. We further explore the mechanics generating SOPTs on the basis of synaptic weight dynamics.展开更多
Both external and endogenous electrical fields widely exist in the environment of cortical neurons. The effects of a weak alternating current （AC） field on a neural network model with synaptic plasticity are studied...Both external and endogenous electrical fields widely exist in the environment of cortical neurons. The effects of a weak alternating current （AC） field on a neural network model with synaptic plasticity are studied. It is found that self-sustained rhythmic firing patterns, which are closely correlated with the cognitive functions, are significantly modified due to the self-organizing of the network in the weak AC field. The activities of the neural networks are affected by the synaptic connection strength, the exterrtal stimuli, and so on. In the presence of learning rules, the synaptic connections can be modulated by the external stimuli, which will further enhance the sensitivity of the network to the external signal. The properties of the external AC stimuli can serve as control parameters in modulating the evolution of the neural network.展开更多
基金supported by the National Key Research and Development Program of China(No.2023YFB4502200)Natural Science Foundation of China(Nos.92164204 and 62374063)the Science and Technology Major Project of Hubei Province(No.2022AEA001).
文摘Memtransistors in which the source-drain channel conductance can be nonvolatilely manipulated through the gate signals have emerged as promising components for implementing neuromorphic computing.On the other side,it is known that the complementary metal-oxide-semiconductor(CMOS)field effect transistors have played the fundamental role in the modern integrated circuit technology.Therefore,will complementary memtransistors(CMT)also play such a role in the future neuromorphic circuits and chips?In this review,various types of materials and physical mechanisms for constructing CMT(how)are inspected with their merits and need-to-address challenges discussed.Then the unique properties(what)and poten-tial applications of CMT in different learning algorithms/scenarios of spiking neural networks(why)are reviewed,including super-vised rule,reinforcement one,dynamic vision with in-sensor computing,etc.Through exploiting the complementary structure-related novel functions,significant reduction of hardware consuming,enhancement of energy/efficiency ratio and other advan-tages have been gained,illustrating the alluring prospect of design technology co-optimization(DTCO)of CMT towards neuro-morphic computing.
基金the National Key Research and Development Program of China,No.2020YFC2004202(to DSX)the National Natural Science Foundation of China(General Program),Nos.81772453,81974358(to DSX)Scientific Research Project of Yangzhi Rehabilitation Hospital Affliated to Tongji University,No.KYPY202006(to TTS)。
文摘Classic paired associative stimulation can improve synaptic plasticity,as demonstrated by animal expe riments and human clinical trials in spinal cord injury patients.Paired associative magnetic stimulation(dual-target peripheral and central magnetic stimulation)has been shown to promote neurologic recove ry after stroke.However,it remains unclear whether paired associative magnetic stimulation can promote recovery of lower limb motor dysfunction after spinal cord injury.We hypothesize that the curre nt caused by central and peripheral magnetic stimulation will conve rge at the synapse,which will promote synapse function and improve the motor function of the relevant muscles.Therefore,this study aimed to examine the effects of paired associative magnetic stimulation on neural circuit activation by measuring changes in motor evoked and somatosensory evoked potentials,motor and sensory function of the lower limbs,functional health and activities of daily living,and depression in patients with spinal co rd injury.We will recruit 110 thora cic spinal trauma patients treated in the Department of Spinal Cord Injury,China Rehabilitation Hospital and randomly assign them to expe rimental and control groups in a 1:1 ratio.The trial group(n=55)will be treated with paired associative magnetic stimulation and conventional rehabilitation treatment.The control group(n=55)will be treated with sham stimulation and co nventional rehabilitation treatment.Outcomes will be measured at four time points:baseline and 4,12,and 24 wee ks after the start of inte rvention(active or sham paired associative magnetic stimulation).The primary outcome measure of this trial is change in lower limb American Spinal Injury Association Impairment Scale motor function score from baseline to last follow-up.Secondary outcome measures include changes in lower limb American Spinal Injury Association sensory function sco re,motor evoked potentials,sensory evoked potentials,modified Ashwo rth scale score,Maslach Burnout Invento ry score,and Hamilton Depres
基金supported by Beijing Natural Science Foundation Key Program(Grant No.Z190007)Beijing Natural Science Foundation(Grant No.2212048)+1 种基金the National Natural Science Foundation of China(Grant Nos.11474272,61774144,and 12004212)the Chinese Academy of Sciences(Grant Nos.QYZDY-SSW-JSC020,XDB28000000,and XDB44000000)。
文摘Current-induced multilevel magnetization switching in ferrimagnetic spintronic devices is highly pursued for the application in neuromorphic computing.In this work,we demonstrate the switching plasticity in Co/Gd ferrimagnetic multilayers where the binary states magnetization switching induced by spin–orbit toque can be tuned into a multistate one as decreasing the domain nucleation barrier.Therefore,the switching plasticity can be tuned by the perpendicular magnetic anisotropy of the multilayers and the in-plane magnetic field.Moreover,we used the switching plasticity of Co/Gd multilayers for demonstrating spike timing-dependent plasticity and sigmoid-like activation behavior.This work gives useful guidance to design multilevel spintronic devices which could be applied in high-performance neuromorphic computing.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11135001 and 11174034)
文摘Phase transitions widely exist in nature and occur when some control parameters are changed. In neural systems, their macroscopic states are represented by the activity states of neuron populations, and phase transitions between different activity states are closely related to corresponding functions in the brain. In particular, phase transitions to some rhythmic synchronous firing states play significant roles on diverse brain functions and disfunctions, such as encoding rhythmical external stimuli, epileptic seizure, etc. However, in previous studies, phase transitions in neuronal networks are almost driven by network parameters （e.g., external stimuli）, and there has been no investigation about the transitions between typical activity states of neuronal networks in a self-organized way by applying plastic connection weights. In this paper, we discuss phase transitions in electrically coupled and lattice-based small-world neuronal networks （LBSW networks） under spike-timing-dependent plasticity （STDP）. By applying STDP on all electrical synapses, various known and novel phase transitions could emerge in LBSW networks, particularly, the phenomenon of self-organized phase transitions （SOPTs）： repeated transitions between synchronous and asynchronous firing states. We further explore the mechanics generating SOPTs on the basis of synaptic weight dynamics.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 61072012, 60901035, 50907044, and 61172009)
文摘Both external and endogenous electrical fields widely exist in the environment of cortical neurons. The effects of a weak alternating current （AC） field on a neural network model with synaptic plasticity are studied. It is found that self-sustained rhythmic firing patterns, which are closely correlated with the cognitive functions, are significantly modified due to the self-organizing of the network in the weak AC field. The activities of the neural networks are affected by the synaptic connection strength, the exterrtal stimuli, and so on. In the presence of learning rules, the synaptic connections can be modulated by the external stimuli, which will further enhance the sensitivity of the network to the external signal. The properties of the external AC stimuli can serve as control parameters in modulating the evolution of the neural network.
