Search · four archives
Search · four archives
14 papers · ranked by Valyu relevance
Chih-Hsu Huang, Chou-Ching K. Lin
Nowadays, building low-dimensional mean-field models of neuronal populations is still a critical issue in the computational neuroscience community, because their derivation is difficult for realistic networks of neurons with conductance-based interactions and spike-frequency adaptation that generate nonlinear…
Richard Gast, Daniel Rose, Harald E. Möller, Nikolaus Weiskopf + 1 more
In neuroscience, computational modeling has become an important source of insight into brain states and dynamics. A basic requirement for computational modeling studies is the availability of efficient software for setting up models and performing numerical simulations. While many such tools exist for different…
Tilo Schwalger, Anton V. Chizhov
- Generalized integrate-and-fire (GIF) models permit efficient extraction of point neuron parameters, which reproduce the spiking behavior of multiple cell types and are available from a public database. - Populations of GIF or conductance-based neuron models can be described by a single state variable – the "time…
Szilvia Szeier, Henrik Jörntell
Behavior ultimately depends on the spatiotemporal patterns of the neuron population activity across the brain. Here we address the issue of how the evolving patterns of population activity can be governed by the intrinsically available mechanisms within the brain. We show how the control of the evolving activity can be…
Tilo Schwalger, Moritz Deger, Wulfram Gerstner
Neural population equations such as neural mass or field models are widely used to study brain activity on a large scale. However, the relation of these models to the properties of single neurons is unclear. Here we derive an equation for several interacting populations at the mesoscopic scale starting from a…
Marc de Kamps, Mikkel Lepperød, Yi Ming Lai
The importance of a mesoscopic description level of the brain has now been well established. Rate based models are widely used, but have limitations. Recently, several extremely efficient population-level methods have been proposed that go beyond the characterization of a population in terms of a single variable. Here…
Mi Lu, Trung Le, Tianxing He, Eli Shlizerman + 1 more
Neurons can display highly variable dynamics. While such variability presumably supports the wide range of behaviors generated by the organism, their gene expressions are relatively stable in the adult brain. This suggests that neuronal activity is a combination of its time-invariant identity and the inputs the neuron…
Blake J. Cook, Andre D. H. Peterson, Wessel Woldman, John R. Terry
Mathematical modelling of the macroscopic electrical activity of the brain is highly nontrivial and requires a detailed understanding of not only the associated mathematical techniques, but also the underlying physiology and anatomy. Neural field theory is a population-level approach to modelling the non-linear…
Daniel Gandolfo, Roger Rodriguez, Henry C. Tuckwell
We investigate the dynamics of large-scale interacting neural populations, composed of conductance based, spiking model neurons with modifiable synaptic connection strengths, which are possibly also subjected to external noisy currents. The network dynamics is controlled by a set of neural population probability…
Maurizio Mattia
Starting from a spectral expansion of the Fokker-Plank equation for the membrane potential density in a network of spiking neurons, a low-dimensional dynamics of the collective firing rate is derived. As a result a n-order ordinary differential equation for the network activity can be worked out by taking into account…
Stefano Luccioli, Eshel Ben‐Jacob, Ari Barzilai, P. Bonifazi + 1 more
'Alessandro Torcini'] It has recently been discovered that single neuron stimulation can impact network dynamics in immature and adult neuronal circuits. Here we report a novel mechanism which can explain in neuronal circuits, at an early stage of development, the peculiar role played by a few specific neurons in…
Yu Wu, Wenlian Lu, Wei Lin, Gareth Leng + 1 more
Yu Wu∗ , Wenlian Lu∗ , Wei Lin∗ , Gareth Leng† , Jianfeng Feng∗,‡ ∗ Centre for Computational Systems Biology and School of Mathematics, Fudan University, PR China † School of Biomedicine, Edinburgh University, UK ‡ Centre for Scientific Computing and Computer Science, Warwick University, UK e-mail: jffeng@fudan.edu.cn…
S. Luccioli, A. Barzilai, E. Ben-Jacob, P. Bonifazi + 1 more
We consider a sparse random network of excitatory leaky integrate-andfire neurons with short-term synaptic depression. Furthermore to mimic the dynamics of a brain circuit in its first stages of development we introduce for each neuron correlations among in-degree and out-degree as well as among excitability and the…
Chenfei Zhang, David Hofmann, Andreas Neef, Fred Wolf
Populations of cortical neurons respond to common input within a millisecond. Morphological features and active ion channel properties were suggested to contribute to this astonishing processing speed. Here we report an exhaustive study of ultrafast population coding for varying axon initial segment (AIS) location…