Network state transitions under deep brain stimulation: A Wilson-Cowan model of Parkinson's Disease [0.03%]
深脑刺激下的帕金森病网络状态转换：一种Wilson–Cowan模型
Aditya Robin Singh,Phool Singh
Aditya Robin Singh
Parkinson's disease is characterized by pathological beta-band oscillations ([Formula: see text]) arising from dopamine-depletion-induced instability in the basal ganglia-thalamocortical network. Although deep brain stimulation of the subth...
Task-Parametrized dynamics: Representation of time and decisions in recurrent neural networks [0.03%]
任务参数化动力学：递归神经网络中的时间和决策表示方法
Cecilia Jarne,Ryeongkyung Yoon,Tahra Eissa et al.
Cecilia Jarne et al.
How do recurrent neural networks (RNNs) internally represent elapsed time to initiate responses after learned delays? To address this question, we trained RNNs on delayed decision-making tasks with progressively increasing temporal demands,...
Embedding of low-dimensional sensory dynamics in recurrent networks: Implications for the geometry of neural representation [0.03%]
低维感觉动态在循环网络中的嵌入：对神经表示几何结构的影响
Vikas N O&#x;Reilly-Shah,Alessandro Maria Selvitella
Vikas N O&#x;Reilly-Shah
Neural population activity in sensory cortex is organized on low-dimensional manifolds, but it is unclear why such manifolds should arise and what determines their geometry. We address this sensory representation problem by modeling cortica...
Embedding of low-dimensional sensory dynamics in recurrent networks: Implications for the geometry of neural representation [0.03%]
低维感觉动力学在递归网络中的嵌入：对神经元表示几何结构的意义
Vikas N O&#x;Reilly-Shah,Alessandro Maria Selvitella
Vikas N O&#x;Reilly-Shah
Neural population activity in sensory cortex is organized on low-dimensional manifolds, but it is unclear why such manifolds should arise and what determines their geometry. We address this sensory representation problem by modeling cortica...
Detailed study of bifurcations in a rate model with excitatory and inhibitory neurons and adaptation [0.03%]
具有适应性的兴奋性和抑制性神经元率模型中的分岔详细研究
Anita Windisch,Péter L Simon
Anita Windisch
The dynamical behaviour of a population-based rate model with firing adaptation is studied. An excitatory and inhibitory population of neurons is recurrently coupled and a negative feedback term is added to the excitatory population as firi...
A spatially discretized convolutional neural mass model for studying meso-scale spatio-temporal transformations in the rat hippocampus [0.03%]
一种用于研究空间离散化的大鼠海马神经质量模型中的时空变换的卷积模型
Duy-Tan J Pham,Gene J Yu,Gianluca Lazzi et al.
Duy-Tan J Pham et al.
The brain operates across multiple spatial and temporal scales, necessitating computationally efficient models that link micro-scale mechanisms to meso- and macro-scale dynamics. Here, we introduce a novel convolutional neural mass model (C...
Estimating latent neuronal nonlinear dynamics by sequential Monte Carlo method and sparse modeling [0.03%]
基于序列蒙特卡洛方法和稀疏建模估计潜在神经非线性动力学
Nodoka Motonishi,Toshiaki Omori
Nodoka Motonishi
Understanding complex neuronal behavior in our brain requires accurate estimation of neuronal models from observed time-series data. In this study, we propose a data-driven sparse modeling method to estimate multi-dimensional latent variabl...
Partha Ghose,Dimitris Pinotsis
Partha Ghose
We propose two experiments for identifying quantum markers in neural data based on quantum variants of well-known equations for neural activity that describe electrical signal propagation on axonal arbors and dendrites. These include (i) te...
Histamine regulation in shaping spindle refractoriness: a computational modeling study [0.03%]
组胺调节塑造纺锤体迟滞性的计算模型研究
Bo Wang,Qiang Li,Wen-Hua Wang et al.
Bo Wang et al.
The spindle refractory period refers to the interval following a spindle during which another spindle does not occur. Lengthening of the spindle refractory period (SRPL) is commonly observed in EEG recordings of patients with neuropsychiatr...
An astro-neural-field model with application to cortical spreading depolarization [0.03%]
一种应用于皮层扩散性去极化的astro-神经-场模型
E Baspinar,D Avitabile,C Nouveau et al.
E Baspinar et al.
We present a novel astro-neural-field population model with application to migraine-related cortical spreading depolarization. The model is composed of four spatio-temporal state variables: excitatory and inhibitory membrane potentials, ast...