Linearization of excitatory synaptic integration at no extra cost

@article{Morel2017LinearizationOE,
  title={Linearization of excitatory synaptic integration at no extra cost},
  author={D. Morel and Chandan Singh and W. Levy},
  journal={Journal of Computational Neuroscience},
  year={2017},
  volume={44},
  pages={173-188}
}
  • D. Morel, Chandan Singh, W. Levy
  • Published 2017
  • Mathematics, Medicine, Computer Science
  • Journal of Computational Neuroscience
  • In many theories of neural computation, linearly summed synaptic activation is a pervasive assumption for the computations performed by individual neurons. Indeed, for certain nominally optimal models, linear summation is required. However, the biophysical mechanisms needed to produce linear summation may add to the energy-cost of neural processing. Thus, the benefits provided by linear summation may be outweighed by the energy-costs. Using voltage-gated conductances in a relatively simple… CONTINUE READING

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 72 REFERENCES
    Linear Summation of Excitatory Inputs by CA1 Pyramidal Neurons
    298
    The cost of linearization
    8
    Amplification and linearization of distal synaptic input to cortical pyramidal cells.
    133
    Dendritic integration of excitatory synaptic input
    574
    Arithmetic of Subthreshold Synaptic Summation in a Model CA1 Pyramidal Cell
    394
    Energy-Efficient Neuronal Computation via Quantal Synaptic Failures
    128
    Dendritic I h normalizes temporal summation in hippocampal CA 1 neurons
    93
    Somatic EPSP amplitude is independent of synapse location in hippocampal pyramidal neurons
    557
    A Mathematical Theory of Energy Efficient Neural Computation and Communication
    49
    Linearity of synaptic interactions in the assembly of receptive fields in cat visual cortex
    50