Adaptive exponential integrate-and-fire model as an effective description of neuronal activity
- PMID: 16014787
- DOI: 10.1152/jn.00686.2005
Adaptive exponential integrate-and-fire model as an effective description of neuronal activity
Abstract
We introduce a two-dimensional integrate-and-fire model that combines an exponential spike mechanism with an adaptation equation, based on recent theoretical findings. We describe a systematic method to estimate its parameters with simple electrophysiological protocols (current-clamp injection of pulses and ramps) and apply it to a detailed conductance-based model of a regular spiking neuron. Our simple model predicts correctly the timing of 96% of the spikes (+/-2 ms) of the detailed model in response to injection of noisy synaptic conductances. The model is especially reliable in high-conductance states, typical of cortical activity in vivo, in which intrinsic conductances were found to have a reduced role in shaping spike trains. These results are promising because this simple model has enough expressive power to reproduce qualitatively several electrophysiological classes described in vitro.
Similar articles
-
Predicting spike times of a detailed conductance-based neuron model driven by stochastic spike arrival.J Physiol Paris. 2004 Jul-Nov;98(4-6):442-51. doi: 10.1016/j.jphysparis.2005.09.010. Epub 2005 Nov 7. J Physiol Paris. 2004. PMID: 16274972
-
Generalized integrate-and-fire models of neuronal activity approximate spike trains of a detailed model to a high degree of accuracy.J Neurophysiol. 2004 Aug;92(2):959-76. doi: 10.1152/jn.00190.2004. J Neurophysiol. 2004. PMID: 15277599
-
How synapses in the auditory system wax and wane: theoretical perspectives.Biol Cybern. 2003 Nov;89(5):318-32. doi: 10.1007/s00422-003-0437-3. Epub 2003 Nov 28. Biol Cybern. 2003. PMID: 14669012 Review.
-
Different types of noise in leaky integrate-and-fire model of neuronal dynamics with discrete periodical input.Gen Physiol Biophys. 2004 Mar;23(1):21-38. Gen Physiol Biophys. 2004. PMID: 15270127
-
A review of the integrate-and-fire neuron model: I. Homogeneous synaptic input.Biol Cybern. 2006 Jul;95(1):1-19. doi: 10.1007/s00422-006-0068-6. Epub 2006 Apr 19. Biol Cybern. 2006. PMID: 16622699 Review.
Cited by
-
Exploring neural oscillations during speech perception via surrogate gradient spiking neural networks.Front Neurosci. 2024 Sep 25;18:1449181. doi: 10.3389/fnins.2024.1449181. eCollection 2024. Front Neurosci. 2024. PMID: 39385848 Free PMC article.
-
How adaptation shapes spike rate oscillations in recurrent neuronal networks.Front Comput Neurosci. 2013 Feb 27;7:9. doi: 10.3389/fncom.2013.00009. eCollection 2013. Front Comput Neurosci. 2013. PMID: 23450654 Free PMC article.
-
Biological learning curves outperform existing ones in artificial intelligence algorithms.Sci Rep. 2019 Aug 9;9(1):11558. doi: 10.1038/s41598-019-48016-4. Sci Rep. 2019. PMID: 31399614 Free PMC article.
-
Assessing brain state and anesthesia level with two-photon calcium signals.Sci Rep. 2023 Feb 23;13(1):3183. doi: 10.1038/s41598-023-30224-8. Sci Rep. 2023. PMID: 36823228 Free PMC article.
-
A spiking neural network model of the Superior Colliculus that is robust to changes in the spatial-temporal input.Sci Rep. 2022 Apr 28;12(1):6916. doi: 10.1038/s41598-022-10991-6. Sci Rep. 2022. PMID: 35484389 Free PMC article.
MeSH terms
LinkOut - more resources
Full Text Sources
Other Literature Sources
Molecular Biology Databases
