- Poster presentation
- Open Access
Predictions of energy efficient Berger-Levy model neurons with constraints
© Ghavami et al; licensee BioMed Central Ltd. 2013
- Published: 8 July 2013
- Mutual Information
- Firing Rate
- Probability Distribution Function
- Model Neuron
- Conditional Probability Distribution
Information theory has been extensively applied to neuroscience problems. The mutual information between input and output has been postulated as an objective, which neuronal systems may optimize. However, only recently the energy efficiency has been addressed within an information-theoretic framework . Here, the key idea is to consider capacity per unit cost (measured in bits per joule, bpj) as the objective. We are interested in how biologically plausible constraints affect predictions made by this new theory for bpj-maximizing model neurons.
This research has been supported in part by the DAAD (German-Arabic/Iranian Higher Education Dialogue).
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