Cognitive Neurodynamics最新文献_第5页

Controlling Alzheimer’s disease by deep brain stimulation based on a data-driven cortical network model 基于数据驱动的皮层网络模型，通过深部脑刺激控制阿尔茨海默病

IF 3.7 3区工程技术

Cognitive Neurodynamics Pub Date : 2024-07-08 DOI: 10.1007/s11571-024-10148-3

SiLu Yan, XiaoLi Yang, ZhiXi Duan

{"title":"Controlling Alzheimer’s disease by deep brain stimulation based on a data-driven cortical network model","authors":"SiLu Yan, XiaoLi Yang, ZhiXi Duan","doi":"10.1007/s11571-024-10148-3","DOIUrl":"https://doi.org/10.1007/s11571-024-10148-3","url":null,"abstract":"This work aims to explore the control effect of DBS on Alzheimer's disease (AD) from a neurocomputational perspective. Firstly, a data-driven cortical network model is constructed using the Diffusion Tensor Imaging data. Then, a typical electrophysiological feature of EEG slowing in AD is reproduced by reducing the synaptic connectivity parameters. The corresponding changes in kinetic behavior mainly include an oscillation decrease in the amplitude and frequency of the pyramidal neuron population. Subsequently, DBS current with specific parameters is introduced into three potential targets of the hippocampus, the nucleus accumbens and the olfactory tubercle, respectively. The results indicate that applying DBS to simulated mild AD patients induces an increase in relative alpha power, a decrease in relative theta power, and a significant rightward shift of the dominant frequency. This is consistent with the EEG reversal in pharmacological treatments for AD. Further, the optimal stimulation strategy of DBS is investigated through spectral and statistical analyses. Specifically, the pathological symptoms of AD could be alleviated by adjusting the critical parameters of DBS, and the control effect of DBS on various targets is that the hippocampus is superior to the olfactory tubercle and nucleus accumbens. Finally, using correlation analysis between the power increments and the nodal degrees, it is concluded that the control effect of DBS is related to the importance of the nodes in the brain network. This study provides a theoretical guidance for determining DBS targets and parameters, which may have a substantial impact on the development of DBS treatment for AD.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141566667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multi-scale modeling to investigate the effects of transcranial magnetic stimulation on morphologically-realistic neuron with depression 多尺度建模研究经颅磁刺激对形态逼真的抑郁神经元的影响

IF 3.7 3区工程技术

Cognitive Neurodynamics Pub Date : 2024-07-03 DOI: 10.1007/s11571-024-10142-9

Licong Li, Shuaiyang Zhang, Hongbo Wang, Fukuan Zhang, Bin Dong, Jianli Yang, Xiuling Liu

{"title":"Multi-scale modeling to investigate the effects of transcranial magnetic stimulation on morphologically-realistic neuron with depression","authors":"Licong Li, Shuaiyang Zhang, Hongbo Wang, Fukuan Zhang, Bin Dong, Jianli Yang, Xiuling Liu","doi":"10.1007/s11571-024-10142-9","DOIUrl":"https://doi.org/10.1007/s11571-024-10142-9","url":null,"abstract":"Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation technique to activate or inhibit the activity of neurons, and thereby regulate their excitability. This technique has demonstrated potential in the treatment of neuropsychiatric disorders, such as depression. However, the effect of TMS on neurons with different severity of depression is still unclear, limiting the development of efficient and personalized clinical application parameters. In this study, a multi-scale computational model was developed to investigate and quantify the differences in neuronal responses to TMS with different degrees of depression. The microscale neuronal models we constructed represent the hippocampal CA1 region in rats under normal conditions and with varying severities of depression (mild, moderate, and major depressive disorder). These models were then coupled to a macroscopic TMS-induced E-Fields model of a rat head comprising multiple types of tissue. Our results demonstrate alterations in neuronal membrane potential and calcium concentration across varying levels of depression severity. As depression severity increases, the peak membrane potential and polarization degree of neuronal soma and dendrites gradually decline, while the peak calcium concentration decreases and the peak arrival time prolongs. Concurrently, the electric fields thresholds and amplification coefficient gradually rise, indicating an increasing difficulty in activating neurons with depression. This study offers novel insights into the mechanisms of magnetic stimulation in depression treatment using multi-scale computational models. It underscores the importance of considering depression severity in treatment strategies, promising to optimize TMS therapeutic approaches.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141523665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Setting a double-capacitive neuron coupled with Josephson junction and piezoelectric source 设置与约瑟夫森结和压电源耦合的双电容神经元

IF 3.7 3区工程技术

Cognitive Neurodynamics Pub Date : 2024-07-02 DOI: 10.1007/s11571-024-10145-6

Yixuan Chen, Feifei Yang, Guodong Ren, Chunni Wang

{"title":"Setting a double-capacitive neuron coupled with Josephson junction and piezoelectric source","authors":"Yixuan Chen, Feifei Yang, Guodong Ren, Chunni Wang","doi":"10.1007/s11571-024-10145-6","DOIUrl":"https://doi.org/10.1007/s11571-024-10145-6","url":null,"abstract":"Perception of voice means acoustic electric conversion in the auditory system, and changes of external magnetic field can affect the neural activities by taming the channel current via some field components including memristor and Josephson junction. Combination of two capacitors via an electric component is effective to describe the physical property of artificial cell membrane, which is often used to reproduce the characteristic of electric activities in cell membrane. Involvement of two capacitive variables for two capacitors in the neural circuit can discern the effect of field diversity in the media in two sides of the cell membrane in theoretical way. A Josephson junction is used to couple a piezoelectric neural circuit composed of two capacitors, one inductor and one nonlinear resistor. Field energy is mainly kept in the capacitive and inductive components, and it is obtained and converted into dimensionless energy function. The Hamilton energy function in an equivalent auditory neuron is verified by using the Helmholtz theorem. Noisy excitation on the neural circuit can be detected via the Josephson junction channel and similar stochastic resonance is detected by regulating the noise intensity, as a result, the average energy reaches a peak value under stochastic resonance. An adaptive law controls the bifurcation parameter, which is relative to the membrane property, and energy shift controls the mode selection during continuous growth of the bifurcation parameter. That is, external energy injection derived from acoustic wave or magnetic field will control the energy level, and then suitable firing patterns are controlled effectively.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141523667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Vagus nerve electrical stimulation in the recovery of upper limb motor functional impairment after ischemic stroke 迷走神经电刺激在缺血性中风后上肢运动功能障碍恢复中的作用

IF 3.7 3区工程技术

Cognitive Neurodynamics Pub Date : 2024-07-01 DOI: 10.1007/s11571-024-10143-8

Long Chen, Huixin Gao, Zhongpeng Wang, Bin Gu, Wanqi Zhou, Meijun Pang, Kuo Zhang, Xiuyun Liu, Dong Ming

{"title":"Vagus nerve electrical stimulation in the recovery of upper limb motor functional impairment after ischemic stroke","authors":"Long Chen, Huixin Gao, Zhongpeng Wang, Bin Gu, Wanqi Zhou, Meijun Pang, Kuo Zhang, Xiuyun Liu, Dong Ming","doi":"10.1007/s11571-024-10143-8","DOIUrl":"https://doi.org/10.1007/s11571-024-10143-8","url":null,"abstract":"Ischemic stroke (IS) is characterized by high mortality, disability rates, and a high risk of recurrence. Motor dysfunction, such as limb hemiparesis, dysphagia, auditory disorders, and speech disorders, usually persists after stroke, which imposes a heavy burden on society and the health care system. Traditional rehabilitation therapies may be ineffective in promoting functional recovery after stroke, and alternative strategies are urgently needed. The Food and Drug Administration (FDA) has approved invasive vagus nerve stimulation (iVNS) for the improvement of refractory epilepsy, treatment-resistant depression, obesity, and moderate to severe upper limb motor impairment following chronic ischemic stroke. Additionally, the FDA has approved transcutaneous vagus nerve stimulation (tVNS) for the improvement of cluster headaches and acute migraines. Recent studies have demonstrated that vagus nerve stimulation (VNS) has neuroprotective effects in both transient and permanent cerebral ischemia animal models, significantly improving upper limb motor impairments, auditory deficits, and swallowing difficulties. Firstly, this article reviews two potential neuronal death pathways following IS, including autophagy and inflammatory responses. Then delves into the current status of preclinical and clinical research on the functional recovery following IS with VNS, as well as the potential mechanisms mediating its neuroprotective effects. Finally, the optimal parameters and timing of VNS application are summarized, and the future challenges and directions of VNS in the treatment of IS are discussed. The application of VNS in stroke rehabilitation research has reached a critical stage, and determining how to safely and effectively translate this technology into clinical practice is of utmost importance. Further preclinical and clinical studies are needed to elucidate the therapeutic mechanisms of VNS.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141529971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Investigating the impact of hearing loss on attentional networks among older individuals: an event-related potential study 调查听力损失对老年人注意力网络的影响：事件相关电位研究

IF 3.7 3区工程技术

Cognitive Neurodynamics Pub Date : 2024-06-21 DOI: 10.1007/s11571-024-10140-x

Sankalpa Madashetty, Hari Prakash Palaniswamy, Bellur Rajashekhar

{"title":"Investigating the impact of hearing loss on attentional networks among older individuals: an event-related potential study","authors":"Sankalpa Madashetty, Hari Prakash Palaniswamy, Bellur Rajashekhar","doi":"10.1007/s11571-024-10140-x","DOIUrl":"https://doi.org/10.1007/s11571-024-10140-x","url":null,"abstract":"Attention is a core cognitive domain crucial in facilitating day-to-day life. Using an attention network test (ANT) along with event-related potentials (ERPs) in older individuals with hearing loss would provide excellent information about the impact of hearing loss on attentional processes. Thus, the current study aims to understand the attentional deficits and its cortical dynamics in older individuals with and without hearing loss. The study recruited 40 participants, 20 older individuals with hearing loss and 20 age and education-matched controls with normal hearing. All the participants underwent cognitive assessment using ANT with simultaneous 32-channel EEG recording. Results revealed significant impairment in executive attention and subtle alterations in alerting and orienting attention among older individuals with hearing loss compared to their normal-hearing counterparts. These findings suggest the negative impact of hearing loss on attentional networks. In addition, ANT and ERPs provide insight into the underlying neural mechanisms in specific attention network deficits associated with hearing loss.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141509912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Memristive leaky integrate-and-fire neuron and learnable straight-through estimator in spiking neural networks 尖峰神经网络中的 Memristive 渗漏整合发射神经元和可学习直通估计器

IF 3.7 3区工程技术

Cognitive Neurodynamics Pub Date : 2024-06-20 DOI: 10.1007/s11571-024-10133-w

Tao Chen, Chunyan She, Lidan Wang, Shukai Duan

{"title":"Memristive leaky integrate-and-fire neuron and learnable straight-through estimator in spiking neural networks","authors":"Tao Chen, Chunyan She, Lidan Wang, Shukai Duan","doi":"10.1007/s11571-024-10133-w","DOIUrl":"https://doi.org/10.1007/s11571-024-10133-w","url":null,"abstract":"Compared to artificial neural networks (ANNs), spiking neural networks (SNNs) present a more biologically plausible model of neural system dynamics. They rely on sparse binary spikes to communicate information and operate in an asynchronous, event-driven manner. Despite the high heterogeneity of the neural system at the neuronal level, most current SNNs employ the widely used leaky integrate-and-fire (LIF) neuron model, which assumes uniform membrane-related parameters throughout the entire network. This approach hampers the expressiveness of spiking neurons and restricts the diversity of neural dynamics. In this paper, we propose replacing the resistor in the LIF model with a discrete memristor to obtain the heterogeneous memristive LIF (MLIF) model. The memristance of the discrete memristor is determined by the voltage and flux at its terminals, leading to dynamic changes in the membrane time parameter of the MLIF model. SNNs composed of MLIF neurons can not only learn synaptic weights but also adaptively change membrane time parameters according to the membrane potential of the neuron, enhancing the learning ability and expression of SNNs. Furthermore, since the proper threshold of spiking neurons can improve the information capacity of SNNs, a learnable straight-through estimator (LSTE) is proposed. The LSTE, based on the straight-through estimator (STE) surrogate function, features a learnable threshold that facilitates the backward propagation of gradients through neurons firing spikes. Extensive experiments on several popular static and neuromorphic benchmark datasets demonstrate the effectiveness of the proposed MLIF and LSTE, especially on the DVS-CIFAR10 dataset, where we achieved the top-1 accuracy of 84.40(%).","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141509910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Time–frequency–space transformer EEG decoding for spinal cord injury 用于脊髓损伤的时频空间变压器脑电图解码

IF 3.7 3区工程技术

Cognitive Neurodynamics Pub Date : 2024-06-18 DOI: 10.1007/s11571-024-10135-8

Fangzhou Xu, Ming Liu, Xinyi Chen, Yihao Yan, Jinzhao Zhao, Yanbing Liu, Jiaqi Zhao, Shaopeng Pang, Sen Yin, Jiancai Leng, Yang Zhang

{"title":"Time–frequency–space transformer EEG decoding for spinal cord injury","authors":"Fangzhou Xu, Ming Liu, Xinyi Chen, Yihao Yan, Jinzhao Zhao, Yanbing Liu, Jiaqi Zhao, Shaopeng Pang, Sen Yin, Jiancai Leng, Yang Zhang","doi":"10.1007/s11571-024-10135-8","DOIUrl":"https://doi.org/10.1007/s11571-024-10135-8","url":null,"abstract":"Transformer neural networks based on multi-head self-attention are effective in several fields. To capture brain activity on electroencephalographic (EEG) signals and construct an effective pattern recognition model, this paper explores the multi-channel deep feature decoding method utilizing the self-attention mechanism. By integrating inter-channel features with intra-channel features, the self-attention mechanism generates a deep feature vector that encompasses information from all brain activities. In this paper, a time-frequency-spatial domain analysis of motor imagery (MI) based EEG signals from spinal cord injury patients is performed to construct a transformer neural network-based MI classification model. The proposed algorithm is named time-frequency-spatial transformer. The time-frequency and spatial domain feature vectors extracted from the EEG signals are input into the transformer neural network for multiple self-attention depth feature encoding, a peak classification accuracy of 93.56% is attained through the fully connected layer. By constructing the attention matrix brain network, it can be inferred that the channel connections constructed by the attention heads have similarities to the brain networks constructed by the EEG raw signals. The experimental results reveal that the self-attention coefficient brain network holds significant potential for brain activity analysis. The self-attention coefficient brain network can better illustrate correlated connections and show sample differences. Attention coefficient brain networks can provide a more discriminative approach for analyzing brain activity in clinical settings.","PeriodicalId":10500,"journal":{"name":"Cognitive Neurodynamics","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141509911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Intranasal insulin effect on cognitive and/or memory impairment: a systematic review and meta-analysis 鼻内胰岛素对认知和/或记忆障碍的影响：系统回顾和荟萃分析

IF 3.7 3区工程技术

Cognitive Neurodynamics Pub Date : 2024-06-13 DOI: 10.1007/s11571-024-10138-5

M. Gómez-Guijarro, I. Cavero-Redondo, A. Saz-Lara, C. Pascual-Morena, C. Álvarez‐Bueno, Irene Martínez-García

引用次数: 0

A working memory model based on recurrent neural networks using reinforcement learning 基于递归神经网络的强化学习工作记忆模型

IF 3.7 3区工程技术

Cognitive Neurodynamics Pub Date : 2024-06-13 DOI: 10.1007/s11571-024-10137-6

Mengyuan Wang, Yihong Wang, Xuying Xu, Xiaochuan Pan

引用次数: 0

Functional connectivity of EEG motor rhythms after spinal cord injury 脊髓损伤后脑电图运动节律的功能连接性

IF 3.7 3区工程技术

Cognitive Neurodynamics Pub Date : 2024-06-10 DOI: 10.1007/s11571-024-10136-7

Jiancai Leng, Xin Yu, Chongfeng Wang, Jinzhao Zhao, Jianqun Zhu, Xinyi Chen, Zhaoxin Zhu, Xiuquan Jiang, Jiaqi Zhao, Chao Feng, Qingbo Yang, Jianfei Li, Lin Jiang, Fangzhou Xu, Yang Zhang

引用次数: 0