LGMD Variability and logarithmic compression in dendrites (Jones and Gabbiani, 2012, 2012B)


A compartmental model of the LGMD with a simplified, rake shaped, excitatory dendrite. It receives spontaneous input and excitatory and inhibitory synaptic inputs triggered by visual stimuli. It generates realistic responses to looming through the velocity dependent scaling and delay of individual excitatory synaptic inputs, with variability. We use the model to show that the key determinants of output variability are spontaneous input and temporal jitter of the excitatory inputs, rather than variability in magnitude of individual inputs (2012B, J Neurophysiol). We also use the model to analyze the transformation of the excitatory signals through the visual pathway; concluding that the representation of stimulus velocity is transformed from an expansive relationship at the level of the LGMD inputs to a logarithmic one at the level of its membrane potential (2012, J Neurosci).

Model Type: Neuron or other electrically excitable cell

Cell Type(s): Locust Lobula Giant Movement Detector (LGMD) neuron

Currents: I K; I K,Ca; I Calcium

Receptors: Nicotinic; GabaA

Transmitters: Acetylcholine; Gaba

Model Concept(s): Sensory processing; Vision

Simulation Environment: NEURON; MATLAB

Implementer(s): Jones, Peter W [pwjones at cnbc.cmu.edu]

References:

Jones PW, Gabbiani F. (2012). Impact of neural noise on a sensory-motor pathway signaling impending collision. Journal of neurophysiology. 107 [PubMed]

Jones PW, Gabbiani F. (2012). Logarithmic compression of sensory signals within the dendritic tree of a collision-sensitive neuron. The Journal of neuroscience : the official journal of the Society for Neuroscience. 32 [PubMed]


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