Comparison between an exact and a heuristic neural mass model with second-order synapses [0.03%]
具有二阶突触的精确和启发式神经元质量模型之间的比较
Pau Clusella,Elif Köksal-Ersöz,Jordi Garcia-Ojalvo et al.
Pau Clusella et al.
Neural mass models (NMMs) are designed to reproduce the collective dynamics of neuronal populations. A common framework for NMMs assumes heuristically that the output firing rate of a neural population can be described by a static nonlinear...
Variational and phase response analysis for limit cycles with hard boundaries, with applications to neuromechanical control problems [0.03%]
具有硬边界的极限环的变分分析和相位响应分析及其在神经机械控制问题中的应用
Yangyang Wang,Jeffrey P Gill,Hillel J Chiel et al.
Yangyang Wang et al.
Motor systems show an overall robustness, but because they are highly nonlinear, understanding how they achieve robustness is difficult. In many rhythmic systems, robustness against perturbations involves response of both the shape and the ...
Exploration of motion inhibition for the suppression of false positives in biologically inspired small target detection algorithms from a moving platform [0.03%]
基于生物灵感的从运动平台检测微小目标算法中抑制假阳性的运动抑制研究
Aaron Melville-Smith,Anthony Finn,Muhammad Uzair et al.
Aaron Melville-Smith et al.
Detecting small moving targets against a cluttered background in visual data is a challenging task. The main problems include spatio-temporal target contrast enhancement, background suppression and accurate target segmentation. When targets...
Contrast independent biologically inspired translational optic flow estimation [0.03%]
独立的生物启发式译码光学流量估算的对比研究
Phillip S M Skelton,Anthony Finn,Russell S A Brinkworth
Phillip S M Skelton
The visual systems of insects are relatively simple compared to humans. However, they enable navigation through complex environments where insects perform exceptional levels of obstacle avoidance. Biology uses two separable modes of optic f...
Correction: Optimum trajectory learning in musculoskeletal systems with model predictive control and deep reinforcement learning [0.03%]
纠正：基于模型预测控制和深度强化学习的肌骨骼系统最优轨迹学习问题
Berat Denizdurduran,Henry Markram,Marc-Oliver Gewaltig
Berat Denizdurduran
Published Erratum
Biological cybernetics. 2022 Dec;116(5-6):729. DOI:10.1007/s00422-022-00949-2 2022
A dynamic spike threshold with correlated noise predicts observed patterns of negative interval correlations in neuronal spike trains [0.03%]
动态阈值与相关噪声预测神经脉冲列中观察到的负区间相关性模式
Robin S Sidhu,Erik C Johnson,Douglas L Jones et al.
Robin S Sidhu et al.
Negative correlations in the sequential evolution of interspike intervals (ISIs) are a signature of memory in neuronal spike-trains. They provide coding benefits including firing-rate stabilization, improved detectability of weak sensory si...
Correction: Optimum trajectory learning in musculoskeletal systems with model predictive control and deep reinforcement learning [0.03%]
纠正：基于模型预测控制和深度强化学习的肌骨骼系统最优轨迹学习问题
Berat Denizdurduran,Henry Markram,Marc-Oliver Gewaltig
Berat Denizdurduran
Published Erratum
Biological cybernetics. 2022 Dec;116(5-6):727. DOI:10.1007/s00422-022-00947-4 2022
Integration of velocity-dependent spatio-temporal structure of place cell activation during navigation in a reservoir model of prefrontal cortex [0.03%]
一种前额叶皮层水库模型在导航过程中整合速度依赖性的空间-时间格局以激活位置细胞
Pablo Scleidorovich,Alfredo Weitzenfeld,Jean-Marc Fellous et al.
Pablo Scleidorovich et al.
Sequential behavior unfolds both in space and in time. The same spatial trajectory can be realized in different manners in the same overall time by changing instantaneous speeds. The current research investigates how speed profiles might be...
Comparison of event-related modulation index and traditional methods for evaluating phase-amplitude coupling using simulated brain signals [0.03%]
基于模拟脑信号比较事件相关调制指数和传统方法评估相幅耦合性能的研究
Chung-Chieh Tsai,Hong-Hsiang Liu,Yi-Li Tseng
Chung-Chieh Tsai
The investigation of brain oscillations and connectivity has become an important topic in the recent decade. There are several types of interactions between neuronal oscillations, and one of the most interesting among these interactions is ...
Biologically plausible single-layer networks for nonnegative independent component analysis [0.03%]
生物逼真的单层网络非负独立成分分析
David Lipshutz,Cengiz Pehlevan,Dmitri B Chklovskii
David Lipshutz
An important problem in neuroscience is to understand how brains extract relevant signals from mixtures of unknown sources, i.e., perform blind source separation. To model how the brain performs this task, we seek a biologically plausible s...