A geometrical solution underlies general neural principle for serial ordering
A general mathematical description of how the brain sequentially encodes knowledge
remains elusive. We propose a linear solution for serial learning tasks, based on the concept …
remains elusive. We propose a linear solution for serial learning tasks, based on the concept …
Lattice physics approaches for neural networks
Modern neuroscience has evolved into a frontier field that draws on numerous disciplines,
resulting in the flourishing of novel conceptual frames primarily inspired by physics and …
resulting in the flourishing of novel conceptual frames primarily inspired by physics and …
Bursting gamma oscillations in neural mass models
Gamma oscillations (30–120 Hz) in the brain are not periodic cycles, but they typically
appear in short-time windows, often called oscillatory bursts. While the origin of this bursting …
appear in short-time windows, often called oscillatory bursts. While the origin of this bursting …
How connection probability shapes fluctuations of neural population dynamics
NE Greven, J Ranft, T Schwalger - arXiv preprint arXiv:2412.16111, 2024 - arxiv.org
Mean-field models of neuronal populations in the brain have proven extremely useful to
understand network dynamics and response to stimuli, but these models generally lack a …
understand network dynamics and response to stimuli, but these models generally lack a …
Inherent trade-off in noisy neural communication with rank-order coding
I Alsolami, T Fukai - Physical Review Research, 2024 - APS
Rank-order coding, a form of temporal coding, has emerged as a promising scheme to
explain the rapid ability of the mammalian brain. Owing to its speed as well as efficiency …
explain the rapid ability of the mammalian brain. Owing to its speed as well as efficiency …
Minimizing information loss reduces spiking neuronal networks to differential equations
J Chang, Z Li, Z Wang, L Tao, ZC Xiao - arXiv preprint arXiv:2411.14801, 2024 - arxiv.org
Spiking neuronal networks (SNNs) are widely used in computational neuroscience, from
biologically realistic modeling of local cortical networks to phenomenological modeling of …
biologically realistic modeling of local cortical networks to phenomenological modeling of …
Escape time in bistable neuronal populations driven by colored synaptic noise
Local networks of neurons are nonlinear systems driven by synaptic currents elicited by its
own spiking activity and the input received from other brain areas. Synaptic currents are well …
own spiking activity and the input received from other brain areas. Synaptic currents are well …
On the physiological and structural contributors to the overall balance of excitation and inhibition in local cortical networks
Overall balance of excitation and inhibition in cortical networks is central to their functionality
and normal operation. Such orchestrated co-evolution of excitation and inhibition is …
and normal operation. Such orchestrated co-evolution of excitation and inhibition is …
Global and local nature of cortical slow waves
Explaining the macroscopic activity of a recorded neuronal population from its known
microscopic properties still poses a great challenge, not just because of the many local …
microscopic properties still poses a great challenge, not just because of the many local …
Rosetta stone for the population dynamics of spiking neuron networks
Populations of spiking neuron models have densities of their microscopic variables (eg,
single-cell membrane potentials) whose evolution fully capture the collective dynamics of …
single-cell membrane potentials) whose evolution fully capture the collective dynamics of …