Biophysics of Computation

@article{2001BiophysicsOC,
  title={Biophysics of Computation},
  author={勇一 作村},
  journal={The Brain \& Neural Networks},
  year={2001},
  volume={8},
  pages={108-108}
}
  • 勇一 作村
  • Published 5 September 2001
  • Physics
  • The Brain & Neural Networks
Cellular and Synaptic Phenotype Compensations Limit Circuit Disruption in Fmr1-KO Mouse Layer 4 Barrel Cortex but Fail to Prevent Deficits in Information Processing
TLDR
It is suggested that it is this developmental loss of layer 4 sensory encoding precision that drives subsequent developmental alterations in layer 4 – layer 2/3 connectivity and plasticity observed in the Fmr1 knockout, and is a critical process producing sensory hypersensitivity.
Synchronization and Inter-Layer Interactions of Noise-Driven Neural Networks
TLDR
This study used the Hodgkin-Huxley (HH) model of neurons to investigate the phase diagram of a developing single-layer neural network and that of a network consisting of two weakly coupled neural layers, and concluded that the repair mechanism has the largest effect for a network with the lognormal neuron positioning and the preferential inter-layer connections.
Rate and Pulse Based Plasticity Governed by Local Synaptic State Variables
TLDR
This paper introduces a formulation of the BCM rule which is based on the instantaneous postsynaptic membrane potential as well as the transmission profile of the presynaptic spike, and can replicate a range of experiments, such as various rate and spike pairing protocols, combinations of the two, aswell as voltage-dependent plasticity.
Thermodynamic constraints on neural dimensions, firing rates, brain temperature and size
  • J. Karbowski
  • Biology
    Journal of Computational Neuroscience
  • 2009
TLDR
It is found that even moderate firing rates cause significant intracellular Na+ build-up, and the ATP consumption rate associated with pumping out these ions grows nonlinearly with frequency, which can lead to the biphasic dependence of brain temperature on frequency as well.
On the design of neural networks in the brain by genetic evolution
Biophysically detailed forward modeling of the neural origin of EEG and MEG signals
Multimodal modeling of neural network activity: computing LFP, ECoG, EEG and MEG signals with LFPy2.0
TLDR
The open-source software LFPy is extended to allow for modeling of networks of multicompartment neurons with concurrent calculations of extracellular potentials and current dipole moments and is shown to show strong scaling performance with different numbers of message-passing interface (MPI) processes, and for different network sizes with different density of connections.
Active subthreshold dendritic conductances shape the local field potential
TLDR
The results show that the L FP signal can give information about the active properties of neurons and imply that preferred frequencies in the LFP can result from those cellular properties instead of, for example, network dynamics.
Information Processing in Brain Modeling: Challenges and Opportunities
TLDR
Challenges of neuronal modeling and analysis are discussed; a mathematical framework of information theory is presented in context of characterizing neuronal behavior.
Focal axonal swellings and associated ultrastructural changes attenuate conduction velocity in central nervous system axons: a computer modeling study
TLDR
The authors' simulations of the consequences of metabolic insult to axons, namely, the appearance of multiple swollen regions, accompanied by perturbation of overlying myelin and increased axolemmal permeability, contained within a single INR, revealed that conduction block occurred when the dimensions of the simulated swellings were within the limits of those measured experimentally.
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