Journal of Computational Neuroscience最新文献_第2页

Cortical dynamics of neural-connectivity fields. 神经连通性领域的皮质动力学。

IF 1.5 4区医学

Journal of Computational Neuroscience Pub Date : 2025-06-01 Epub Date: 2025-04-10 DOI: 10.1007/s10827-025-00903-8

Gerald K Cooray, Vernon Cooray, Karl J Friston

引用次数: 0

Inferring collective synchrony observing spiking of one or several neurons. 推断集体同步性观察一个或几个神经元的尖峰。

IF 1.5 4区医学

Journal of Computational Neuroscience Pub Date : 2025-06-01 Epub Date: 2025-03-22 DOI: 10.1007/s10827-025-00900-x

Arkady Pikovsky, Michael Rosenblum

引用次数: 0

Localist neural plasticity identified by mutual information. 通过互信息识别局部神经可塑性

IF 1.5 4区医学

Journal of Computational Neuroscience Pub Date : 2025-06-01 Epub Date: 2025-03-22 DOI: 10.1007/s10827-025-00901-w

Gabriele Scheler, Martin L Schumann, Johann Schumann

{"title":"Localist neural plasticity identified by mutual information.","authors":"Gabriele Scheler, Martin L Schumann, Johann Schumann","doi":"10.1007/s10827-025-00901-w","DOIUrl":"10.1007/s10827-025-00901-w","url":null,"abstract":"We present a model of pattern memory and retrieval with novel, technically useful and biologically realistic properties. Specifically, we enter n variations of k pattern classes (n*k patterns) onto a cortex-like balanced inhibitory-excitatory network with heterogeneous neurons, and let the pattern spread within the recurrent network. We show that we can identify high mutual-information (MI) neurons as major information-bearing elements within each pattern representation. We employ a simple one-shot adaptive (learning) process focusing on high MI neurons and inhibition. Such 'localist plasticity' has high efficiency, because it requires only few adaptations for each pattern. Specifically, we store k=10 patterns of size s=400 in a 1000/1200 neuron network. We stimulate high MI neurons and in this way recall patterns, such that the whole network represents this pattern. We assess the quality of the representation (a) before learning, when entering the pattern into a naive network, (b) after learning, on the adapted network, and (c) after recall by stimulation. The recalled patterns could be easily recognized by a trained classifier. The recalled pattern 'unfolds' over the recurrent network with high similarity to the original input pattern. We discuss the distribution of neuron properties in the network, and find that an initial Gaussian distribution changes into a more heavy-tailed, lognormal distribution during the adaptation process. The remarkable result is that we are able to achieve reliable pattern recall by stimulating only high information neurons. This work provides a biologically-inspired model of cortical memory and may have interesting technical applications.","PeriodicalId":54857,"journal":{"name":"Journal of Computational Neuroscience","volume":" ","pages":"321-331"},"PeriodicalIF":1.5,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143694073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dopamine modulation of basolateral amygdala activity and function. 多巴胺对基底外侧杏仁核活动和功能的调节。

IF 1.5 4区医学

Journal of Computational Neuroscience Pub Date : 2025-06-01 Epub Date: 2025-03-19 DOI: 10.1007/s10827-025-00897-3

Alexey Kuznetsov

{"title":"Dopamine modulation of basolateral amygdala activity and function.","authors":"Alexey Kuznetsov","doi":"10.1007/s10827-025-00897-3","DOIUrl":"10.1007/s10827-025-00897-3","url":null,"abstract":"The basolateral amygdala (BLA) is central to emotional processing, fear learning, and memory. Dopamine (DA) significantly influences BLA function, yet its precise effects are not clear. We present a mathematical model exploring how DA modulation of BLA activity depends on the network's current state. Specifically, we model the firing rates of interconnected neural groups in the BLA and their responses to external stimuli and DA modulation. BLA projection neurons are separated into two groups according to their responses-fear and safety. These groups are connected by mutual inhibition though interneurons. We contrast 'differentiated' BLA states, where fear and safety projection neurons exhibit distinct activity levels, with 'non-differentiated' states. We posit that differentiated states support selective responses and short-term emotional memory. On the other hand, non-differentiated states represent either the case in which BLA is disengaged, or the activation of the fear and safety neurons is at a similar moderate or high level. We show that, while DA further disengages BLA in the low activity state, it destabilizes the moderate activity non-differentiated BLA state. We show that in the latter non-differentiated state the BLA is hypersensitive, and the polarity of its responses (fear or safety) to salient stimuli is highly random. We hypothesize that this non-differentiated state is related to anxiety and Post-Traumatic Stress Disorder (PTSD).","PeriodicalId":54857,"journal":{"name":"Journal of Computational Neuroscience","volume":" ","pages":"359-372"},"PeriodicalIF":1.5,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Axon initial segment plasticity caused by auditory deprivation degrades time difference sensitivity in a model of neural responses to cochlear implants. 听觉剥夺引起的轴突初始段可塑性降低了耳蜗植入神经反应模型的时差敏感性。

IF 1.5 4区医学

Journal of Computational Neuroscience Pub Date : 2025-06-01 Epub Date: 2025-04-17 DOI: 10.1007/s10827-025-00902-9

Anna Jing, Sylvia Xi, Ivan Fransazov, Joshua H Goldwyn

{"title":"Axon initial segment plasticity caused by auditory deprivation degrades time difference sensitivity in a model of neural responses to cochlear implants.","authors":"Anna Jing, Sylvia Xi, Ivan Fransazov, Joshua H Goldwyn","doi":"10.1007/s10827-025-00902-9","DOIUrl":"10.1007/s10827-025-00902-9","url":null,"abstract":"Synaptic and neural properties can change during periods of auditory deprivation. These changes may disrupt the computations that neurons perform. In the brainstem of chickens, auditory deprivation can lead to changes in the size and biophysics of the axon initial segment (AIS) of neurons in the sound source localization circuit. This is the phenomenon of axon initial segment (AIS) plasticity. Individuals who use cochlear implants (CIs) experience periods of hearing loss, and so we ask whether AIS plasticity in neurons of the medial superior olive (MSO), a key stage of sound location processing, would impact time difference sensitivity in the scenario of hearing with cochlear implants. The biophysical changes that we implement in our model of AIS plasticity include enlargement of the AIS and replacement of low-threshold potassium conductance with the more slowly-activated M-type potassium conductance. AIS plasticity has been observed to have a homeostatic effect with respect to excitability. In our model, AIS plasticity has the additional effect of converting MSO neurons from phasic firing type to tonic firing type. Phasic firing is known to have greater temporal sensitivity to coincident inputs. Consistent with this, we find AIS plasticity degrades time difference sensitivity in the auditory deprived MSO neuron model across a range of stimulus parameters. Our study illustrates a possible mechanism of cellular plasticity in a non-peripheral stage of neural processing that could impose barriers to sound source localization by bilateral cochlear implant users.","PeriodicalId":54857,"journal":{"name":"Journal of Computational Neuroscience","volume":" ","pages":"267-288"},"PeriodicalIF":1.5,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12181223/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144065170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A generalized mathematical framework for the calcium control hypothesis describes weight-dependent synaptic plasticity. 钙控制假说的广义数学框架描述了体重依赖的突触可塑性。

IF 1.5 4区医学

Journal of Computational Neuroscience Pub Date : 2025-06-01 Epub Date: 2025-03-18 DOI: 10.1007/s10827-025-00894-6

Toviah Moldwin, Li Shay Azran, Idan Segev

{"title":"A generalized mathematical framework for the calcium control hypothesis describes weight-dependent synaptic plasticity.","authors":"Toviah Moldwin, Li Shay Azran, Idan Segev","doi":"10.1007/s10827-025-00894-6","DOIUrl":"10.1007/s10827-025-00894-6","url":null,"abstract":"The brain modifies synaptic strengths to store new information via long-term potentiation (LTP) and long-term depression (LTD). Evidence has mounted that long-term synaptic plasticity is controlled via concentrations of calcium ([Ca2+]) in postsynaptic dendritic spines. Several mathematical models describe this phenomenon, including those of Shouval, Bear, and Cooper (SBC) (Shouval et al., 2002, 2010) and Graupner and Brunel (GB) (Graupner & Brunel, 2012). Here we suggest a generalized version of the SBC and GB models, the fixed point - learning rate (FPLR) framework, where the synaptic [Ca2+] specifies a fixed point toward which the synaptic weight approaches asymptotically at a [Ca2+]-dependent rate. The FPLR framework offers a straightforward phenomenological interpretation of calcium-based plasticity: the calcium concentration tells the synaptic weight where it is going and how quickly it goes there. The FPLR framework can flexibly incorporate various experimental findings, including the existence of multiple regions of [Ca2+] where no plasticity occurs, or plasticity observed experimentally in cerebellar Purkinje cells, where the directionality of calcium-based synaptic changes is reversed relative to cortical and hippocampal neurons. We also suggest a modeling approach that captures the dependency of late-phase plasticity stabilization on protein synthesis. We demonstrate that due to the asymptotic nature of synaptic changes in the FPLR rule, the plastic changes induced by frequency- and spike-timing-dependent plasticity protocols are weight-dependent. Finally, we show how the FPLR framework can explain the weight-dependence observed in behavioral time scale plasticity (BTSP).","PeriodicalId":54857,"journal":{"name":"Journal of Computational Neuroscience","volume":" ","pages":"333-357"},"PeriodicalIF":1.5,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12181224/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143659511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Biologically realistic mean field model of spiking neural networks with fast and slow inhibitory synapses. 具有快速和慢速抑制性突触的脉冲神经网络的生物现实平均场模型。

IF 1.5 4区医学

Journal of Computational Neuroscience Pub Date : 2025-06-01 Epub Date: 2025-04-23 DOI: 10.1007/s10827-025-00904-7

Claudio Di Geronimo, Alain Destexhe, Matteo Di Volo

{"title":"Biologically realistic mean field model of spiking neural networks with fast and slow inhibitory synapses.","authors":"Claudio Di Geronimo, Alain Destexhe, Matteo Di Volo","doi":"10.1007/s10827-025-00904-7","DOIUrl":"10.1007/s10827-025-00904-7","url":null,"abstract":"We present a mean field model for a spiking neural network of excitatory and inhibitory neurons with fast GABA <math><mmultiscripts><mrow></mrow> <mi>A</mi> <mrow></mrow></mmultiscripts> </math> and nonlinear slow GABA <math><mmultiscripts><mrow></mrow> <mi>B</mi> <mrow></mrow></mmultiscripts> </math> inhibitory conductance-based synapses. This mean field model can predict the spontaneous and evoked response of the network to external stimulation in asynchronous irregular regimes. The model displays theta oscillations for sufficiently strong GABA <math><mmultiscripts><mrow></mrow> <mi>B</mi> <mrow></mrow></mmultiscripts> </math> conductance. Optogenetic activation of interneurons and an increase of GABA <math><mmultiscripts><mrow></mrow> <mi>B</mi> <mrow></mrow></mmultiscripts> </math> conductance caused opposite effects on the emergence of gamma oscillations in the model. In agreement with direct numerical simulations of neural networks and experimental data, the mean field model predicts that an increase of GABA <math><mmultiscripts><mrow></mrow> <mi>B</mi> <mrow></mrow></mmultiscripts> </math> conductance reduces gamma oscillations. Furthermore, the slow dynamics of GABA <math><mmultiscripts><mrow></mrow> <mi>B</mi> <mrow></mrow></mmultiscripts> </math> synapses regulates the appearance and duration of transient gamma oscillations, namely gamma bursts, in the mean field model. Finally, we show that nonlinear GABA <math><mmultiscripts><mrow></mrow> <mi>B</mi> <mrow></mrow></mmultiscripts> </math> synapses play a major role to stabilize the network from the emergence of epileptic seizures.","PeriodicalId":54857,"journal":{"name":"Journal of Computational Neuroscience","volume":" ","pages":"289-303"},"PeriodicalIF":1.5,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143996642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Network effects of traumatic brain injury: from infra slow to high frequency oscillations and seizures. 创伤性脑损伤的网络效应：从低频振荡到高频振荡和癫痫发作。

IF 1.5 4区医学

Journal of Computational Neuroscience Pub Date : 2025-06-01 Epub Date: 2025-02-28 DOI: 10.1007/s10827-025-00895-5

Brianna Marsh, Sylvain Chauvette, Mingxiong Huang, Igor Timofeev, Maxim Bazhenov

{"title":"Network effects of traumatic brain injury: from infra slow to high frequency oscillations and seizures.","authors":"Brianna Marsh, Sylvain Chauvette, Mingxiong Huang, Igor Timofeev, Maxim Bazhenov","doi":"10.1007/s10827-025-00895-5","DOIUrl":"10.1007/s10827-025-00895-5","url":null,"abstract":"Traumatic brain injury (TBI) can have a multitude of effects on neural functioning. In extreme cases, TBI can lead to seizures both immediately following the injury as well as persistent epilepsy over years to a lifetime. However, mechanisms of neural dysfunctioning after TBI remain poorly understood. To address these questions, we analyzed human and animal data and we developed a biophysical network model implementing effects of ion concentration dynamics and homeostatic synaptic plasticity to test effects of TBI on the brain network dynamics. We focus on three primary phenomena that have been reported in vivo after TBI: an increase in infra slow oscillations (<0.1 Hz), increase in Delta power (1 - 4 Hz), and the emergence of broadband Gamma bursts (30 - 100 Hz). Using computational network model, we show that the infra slow oscillations can be directly attributed to extracellular potassium dynamics, while the increase in Delta power and occurrence of Gamma bursts are related to the increase in strength of synaptic weights from homeostatic synaptic scaling triggered by trauma. We also show that the buildup of Gamma bursts in the injured region can lead to seizure-like events that propagate across the entire network; seizures can then be initiated in previously healthy regions. This study brings greater understanding of the network effects of TBI and how they can lead to epileptic activity. This lays the foundation to begin investigating how injured networks can be healed and seizures prevented.","PeriodicalId":54857,"journal":{"name":"Journal of Computational Neuroscience","volume":" ","pages":"247-266"},"PeriodicalIF":1.5,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12181067/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143525251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Neural waves and computation in a neural net model III: preplay, working memory and bursts. 神经网络模型中的神经波和计算III：预演，工作记忆和突发。

IF 1.5 4区医学

Journal of Computational Neuroscience Pub Date : 2025-06-01 Epub Date: 2025-03-17 DOI: 10.1007/s10827-025-00899-1

S A Selesnick

引用次数: 0

Modeling impairment of ionic regulation with extended Adaptive Exponential integrate-and-fire models. 扩展自适应指数积分-火模型对离子调节损伤的建模。

IF 1.5 4区医学

Journal of Computational Neuroscience Pub Date : 2025-03-01 Epub Date: 2025-01-23 DOI: 10.1007/s10827-025-00893-7

Damien Depannemaecker, Federico Tesler, Mathieu Desroches, Viktor Jirsa, Alain Destexhe

引用次数: 0