Journal of Computational Neuroscience最新文献

A cortical field theory - dynamics and symmetries. 皮层场理论--动力学和对称性。

IF 1.5 4区医学

Journal of Computational Neuroscience Pub Date : 2024-10-01 DOI: 10.1007/s10827-024-00878-y

Gerald K Cooray, Vernon Cooray, Karl Friston

{"title":"A cortical field theory - dynamics and symmetries.","authors":"Gerald K Cooray, Vernon Cooray, Karl Friston","doi":"10.1007/s10827-024-00878-y","DOIUrl":"https://doi.org/10.1007/s10827-024-00878-y","url":null,"abstract":"We characterise cortical dynamics using partial differential equations (PDEs), analysing various connectivity patterns within the cortical sheet. This exploration yields diverse dynamics, encompassing wave equations and limit cycle activity. We presume balanced equations between excitatory and inhibitory neuronal units, reflecting the ubiquitous oscillatory patterns observed in electrophysiological measurements. Our derived dynamics comprise lowest-order wave equations (i.e., the Klein-Gordon model), limit cycle waves, higher-order PDE formulations, and transitions between limit cycles and near-zero states. Furthermore, we delve into the symmetries of the models using the Lagrangian formalism, distinguishing between continuous and discontinuous symmetries. These symmetries allow for mathematical expediency in the analysis of the model and could also be useful in studying the effect of symmetrical input from distributed cortical regions. Overall, our ability to derive multiple constraints on the fields - and predictions of the model - stems largely from the underlying assumption that the brain operates at a critical state. This assumption, in turn, drives the dynamics towards oscillatory or semi-conservative behaviour. Within this critical state, we can leverage results from the physics literature, which serve as analogues for neural fields, and implicit construct validity. Comparisons between our model predictions and electrophysiological findings from the literature - such as spectral power distribution across frequencies, wave propagation speed, epileptic seizure generation, and pattern formation over the cortical surface - demonstrate a close match. This study underscores the importance of utilizing symmetry preserving PDE formulations for further mechanistic insights into cortical activity.","PeriodicalId":54857,"journal":{"name":"Journal of Computational Neuroscience","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142332658","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

Computational model of layer 2/3 in mouse primary visual cortex explains observed visuomotor mismatch response. 小鼠初级视觉皮层第 2/3 层的计算模型解释了观察到的视觉运动不匹配反应。

IF 1.5 4区医学

Journal of Computational Neuroscience Pub Date : 2024-09-28 DOI: 10.1007/s10827-024-00882-2

Heiko Hoffmann

引用次数: 0

Formation and retrieval of cell assemblies in a biologically realistic spiking neural network model of area CA3 in the mouse hippocampus 小鼠海马 CA3 区生物仿真尖峰神经网络模型中细胞集合的形成和检索

IF 1.2 4区医学

Journal of Computational Neuroscience Pub Date : 2024-09-17 DOI: 10.1007/s10827-024-00881-3

Jeffrey D. Kopsick, Joseph A. Kilgore, Gina C. Adam, Giorgio A. Ascoli

{"title":"Formation and retrieval of cell assemblies in a biologically realistic spiking neural network model of area CA3 in the mouse hippocampus","authors":"Jeffrey D. Kopsick, Joseph A. Kilgore, Gina C. Adam, Giorgio A. Ascoli","doi":"10.1007/s10827-024-00881-3","DOIUrl":"https://doi.org/10.1007/s10827-024-00881-3","url":null,"abstract":"The hippocampal formation is critical for episodic memory, with area Cornu Ammonis 3 (CA3) a necessary substrate for auto-associative pattern completion. Recent theoretical and experimental evidence suggests that the formation and retrieval of cell assemblies enable these functions. Yet, how cell assemblies are formed and retrieved in a full-scale spiking neural network (SNN) of CA3 that incorporates the observed diversity of neurons and connections within this circuit is not well understood. Here, we demonstrate that a data-driven SNN model quantitatively reflecting the neuron type-specific population sizes, intrinsic electrophysiology, connectivity statistics, synaptic signaling, and long-term plasticity of the mouse CA3 is capable of robust auto-association and pattern completion via cell assemblies. Our results show that a broad range of assembly sizes could successfully and systematically retrieve patterns from heavily incomplete or corrupted cues after a limited number of presentations. Furthermore, performance was robust with respect to partial overlap of assemblies through shared cells, substantially enhancing memory capacity. These novel findings provide computational evidence that the specific biological properties of the CA3 circuit produce an effective neural substrate for associative learning in the mammalian brain.","PeriodicalId":54857,"journal":{"name":"Journal of Computational Neuroscience","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142258234","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

A computational model of auditory chirp-velocity sensitivity and amplitude-modulation tuning in inferior colliculus neurons 下丘神经元听觉啁啾速度敏感性和振幅调制调谐的计算模型

IF 1.2 4区医学

Journal of Computational Neuroscience Pub Date : 2024-09-11 DOI: 10.1007/s10827-024-00880-4

Paul W. Mitchell, Laurel H. Carney

{"title":"A computational model of auditory chirp-velocity sensitivity and amplitude-modulation tuning in inferior colliculus neurons","authors":"Paul W. Mitchell, Laurel H. Carney","doi":"10.1007/s10827-024-00880-4","DOIUrl":"https://doi.org/10.1007/s10827-024-00880-4","url":null,"abstract":"We demonstrate a model of chirp-velocity sensitivity in the inferior colliculus (IC) that retains the tuning to amplitude modulation (AM) that was established in earlier models. The mechanism of velocity sensitivity is sequence detection by octopus cells of the posteroventral cochlear nucleus, which have been proposed in physiological studies to respond preferentially to the order of arrival of cross-frequency inputs of different amplitudes. Model architecture is based on coincidence detection of a combination of excitatory and inhibitory inputs. Chirp-sensitivity of the IC output is largely controlled by the strength and timing of the chirp-sensitive octopus-cell inhibitory input. AM tuning is controlled by inhibition and excitation that are tuned to the same frequency. We present several example neurons that demonstrate the feasibility of the model in simulating realistic chirp-sensitivity and AM tuning for a wide range of characteristic frequencies. Additionally, we explore the systematic impact of varying parameters on model responses. The proposed model can be used to assess the contribution of IC chirp-velocity sensitivity to responses to complex sounds, such as speech.","PeriodicalId":54857,"journal":{"name":"Journal of Computational Neuroscience","volume":null,"pages":null},"PeriodicalIF":1.2,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142192348","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

JCNS goes multiscale. JCNS 走向多尺度。

IF 1.5 4区医学

Journal of Computational Neuroscience Pub Date : 2024-08-26 DOI: 10.1007/s10827-024-00879-x

Alain Destexhe, Jonathan Victor

引用次数: 0

Firing rate models for gamma oscillations in I-I and E-I networks. I-I 和 E-I 网络中伽马振荡的触发率模型。

IF 1.5 4区医学

Journal of Computational Neuroscience Pub Date : 2024-08-19 DOI: 10.1007/s10827-024-00877-z

Yiqing Lu, John Rinzel

{"title":"Firing rate models for gamma oscillations in I-I and E-I networks.","authors":"Yiqing Lu, John Rinzel","doi":"10.1007/s10827-024-00877-z","DOIUrl":"https://doi.org/10.1007/s10827-024-00877-z","url":null,"abstract":"Firing rate models for describing the mean-field activities of neuronal ensembles can be used effectively to study network function and dynamics, including synchronization and rhythmicity of excitatory-inhibitory populations. However, traditional Wilson-Cowan-like models, even when extended to include an explicit dynamic synaptic activation variable, are found unable to capture some dynamics such as Interneuronal Network Gamma oscillations (ING). Use of an explicit delay is helpful in simulations at the expense of complicating mathematical analysis. We resolve this issue by introducing a dynamic variable, u, that acts as an effective delay in the negative feedback loop between firing rate (r) and synaptic gating of inhibition (s). In effect, u endows synaptic activation with second order dynamics. With linear stability analysis, numerical branch-tracking and simulations, we show that our r-u-s rate model captures some key qualitative features of spiking network models for ING. We also propose an alternative formulation, a v-u-s model, in which mean membrane potential v satisfies an averaged current-balance equation. Furthermore, we extend the framework to E-I networks. With our six-variable v-u-s model, we demonstrate in firing rate models the transition from Pyramidal-Interneuronal Network Gamma (PING) to ING by increasing the external drive to the inhibitory population without adjusting synaptic weights. Having PING and ING available in a single network, without invoking synaptic blockers, is plausible and natural for explaining the emergence and transition of two different types of gamma oscillations.","PeriodicalId":54857,"journal":{"name":"Journal of Computational Neuroscience","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142005961","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

Incorporating slow NMDA-type receptors with nonlinear voltage-dependent magnesium block in a next generation neural mass model: derivation and dynamics. 将具有非线性电压依赖性镁阻滞的慢速 NMDA 型受体纳入下一代神经质量模型：推导与动力学。

IF 1.5 4区医学

Journal of Computational Neuroscience Pub Date : 2024-08-01 Epub Date: 2024-07-05 DOI: 10.1007/s10827-024-00874-2

Hiba Sheheitli, Viktor Jirsa

{"title":"Incorporating slow NMDA-type receptors with nonlinear voltage-dependent magnesium block in a next generation neural mass model: derivation and dynamics.","authors":"Hiba Sheheitli, Viktor Jirsa","doi":"10.1007/s10827-024-00874-2","DOIUrl":"10.1007/s10827-024-00874-2","url":null,"abstract":"We derive a next generation neural mass model of a population of quadratic-integrate-and-fire neurons, with slow adaptation, and conductance-based AMPAR, GABAR and nonlinear NMDAR synapses. We show that the Lorentzian ansatz assumption can be satisfied by introducing a piece-wise polynomial approximation of the nonlinear voltage-dependent magnesium block of NMDAR current. We study the dynamics of the resulting system for two example cases of excitatory cortical neurons and inhibitory striatal neurons. Bifurcation diagrams are presented comparing the different dynamical regimes as compared to the case of linear NMDAR currents, along with sample comparison simulation time series demonstrating different possible oscillatory solutions. The omission of the nonlinearity of NMDAR currents results in a shift in the range (and possible disappearance) of the constant high firing rate regime, along with a modulation in the amplitude and frequency power spectrum of oscillations. Moreover, nonlinear NMDAR action is seen to be state-dependent and can have opposite effects depending on the type of neurons involved and the level of input firing rate received. The presented model can serve as a computationally efficient building block in whole brain network models for investigating the differential modulation of different types of synapses under neuromodulatory influence or receptor specific malfunction.","PeriodicalId":54857,"journal":{"name":"Journal of Computational Neuroscience","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11327200/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141536022","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 computational model elucidating mechanisms and variability in theta burst stimulation responses. 阐明θ猝发刺激反应机制和可变性的计算模型。

IF 1.5 4区医学

Journal of Computational Neuroscience Pub Date : 2024-08-01 Epub Date: 2024-08-09 DOI: 10.1007/s10827-024-00875-1

Mohammadreza Vasheghani Farahani, Seyed Peyman Shariatpanahi, Bahram Goliaei

{"title":"A computational model elucidating mechanisms and variability in theta burst stimulation responses.","authors":"Mohammadreza Vasheghani Farahani, Seyed Peyman Shariatpanahi, Bahram Goliaei","doi":"10.1007/s10827-024-00875-1","DOIUrl":"10.1007/s10827-024-00875-1","url":null,"abstract":"Theta burst stimulation (TBS) is a form of repetitive transcranial magnetic stimulation (rTMS) with unknown underlying mechanisms and highly variable responses across subjects. To investigate these issues, we developed a simple computational model. Our model consisted of two neurons linked by an excitatory synapse that incorporates two mechanisms: short-term plasticity (STP) and spike-timing-dependent plasticity (STDP). We applied a variable-amplitude current through I-clamp with a TBS time pattern to the pre- and post-synaptic neurons, simulating synaptic plasticity. We analyzed the results and provided an explanation for the effects of TBS, as well as the variability of responses to it. Our findings suggest that the interplay of STP and STDP mechanisms determines the direction of plasticity, which selectively affects synapses in extended neurons and underlies functional effects. Our model describes how the timing, number, and intensity of pulses delivered to neurons during rTMS contribute to induced plasticity. This not only successfully explains the different effects of intermittent TBS (iTBS) and continuous TBS (cTBS), but also predicts the results of other protocols such as 10 Hz rTMS. We propose that the variability in responses to TBS can be attributed to the variable span of neuronal thresholds across individuals and sessions. Our model suggests a biologically plausible mechanism for the diverse responses to TBS protocols and aligns with experimental data on iTBS and cTBS outcomes. This model could potentially aid in improving TBS and rTMS protocols and customizing treatments for patients, brain areas, and brain disorders.","PeriodicalId":54857,"journal":{"name":"Journal of Computational Neuroscience","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141908396","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

Antiferromagnetic artificial neuron modeling of the withdrawal reflex. 戒断反射的反铁磁人工神经元建模

IF 1.5 4区医学

Journal of Computational Neuroscience Pub Date : 2024-08-01 Epub Date: 2024-07-10 DOI: 10.1007/s10827-024-00873-3

Hannah Bradley, Lily Quach, Steven Louis, Vasyl Tyberkevych

引用次数: 0

Neural waves and computation in a neural net model II: Data-like structures and the dynamics of episodic memory. 神经网络模型中的神经波和计算 II：类似数据的结构和外显记忆的动态变化。

IF 1.5 4区医学

Journal of Computational Neuroscience Pub Date : 2024-08-01 Epub Date: 2024-07-31 DOI: 10.1007/s10827-024-00876-0

Stephen Selesnick

{"title":"Neural waves and computation in a neural net model II: Data-like structures and the dynamics of episodic memory.","authors":"Stephen Selesnick","doi":"10.1007/s10827-024-00876-0","DOIUrl":"10.1007/s10827-024-00876-0","url":null,"abstract":"The computational resources of a neuromorphic network model introduced earlier were investigated in the first paper of this series. It was argued that a form of ubiquitous spontaneous local convolution enabled logical gate-like neural motifs to form into hierarchical feed-forward structures of the Hubel-Wiesel type. Here we investigate concomitant data-like structures and their dynamic rôle in memory formation, retrieval, and replay. The mechanisms give rise to the need for general inhibitory sculpting, and the simulation of the replay of episodic memories, well known in humans and recently observed in rats. Other consequences include explanations of such findings as the directional flows of neural waves in memory formation and retrieval, visual anomalies and memory deficits in schizophrenia, and the operation of GABA agonist drugs in suppressing episodic memories. We put forward the hypothesis that all neural logical operations and feature extractions are of the convolutional hierarchical type described here and in the earlier paper, and exemplified by the Hubel-Wiesel model of the visual cortex, but that in more general cases the precise geometric layering might be obscured and so far undetected.","PeriodicalId":54857,"journal":{"name":"Journal of Computational Neuroscience","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141857226","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