Josef Ladenbauer, Moritz Augustin, Klaus Obermayer
How adaptation currents and synaptic
inhibition change threshold, gain and
variability of neuronal spiking
From Twenty Second Annual Computational Neuroscience Meeting: CNS*2013 Paris,
France. 13-18 July 2013
Conference paper, Published version
This version is available at http://nbn-resolving.de/urn:nbn:de:kobv:83-opus4-69964.
Suggested Citation
Ladenbauer, Josef ; Augustin, Moritz ; Obermayer, Klaus : How adaptation currents and synaptic
inhibition change threshold, gain and variability of neuronal spiking : From Twenty Second Annual
Computational Neuroscience Meeting: CNS*2013 Paris, France. 13-18 July 2013. - In: BMC
Neuroscience. - ISSN 1471-2202 (online). - 14 (2013), suppl. 1, P299. -
doi:10.1186/1471-2202-14-S1-P299.
Terms of Use
This work is licensed under a CC BY 2.0 License (Creative
Commons Attribution 2.0 Generic). For more information see
http://creativecommons.org/licenses/by/2.0.
Powered by TCPDF (www.tcpdf.org)
POSTER PRESENTATION Open Access
How adaptation currents and synaptic inhibition
change threshold, gain and variability of
neuronal spiking
Josef Ladenbauer
1,2*
, Moritz Augustin
1,2
, Klaus Obermayer
1,2
From Twenty Second Annual Computational Neuroscience Meeting: CNS*2013
Paris, France. 13-18 July 2013
Many types of neurons show spike rate adaptation, a
gradual decrease in spiking activity following a sudden
increase in stimulus intensity. This behavior is typically
mediated by slow potassium currents through voltage-
sensitive low-threshold or calcium-activated high-threshold
channels, both of which are susceptible to cholinergic
modulation [1]. Such adaptation currents (and changes
thereof) contribute to frequency selectivity [2], coding [3]
and attention [4]. These effects are likely caused by alter-
ing the relationship between synaptic input and spike
rate output (I-O curve) as well as the characteristics of
inter-spike intervals (ISI). Here we investigate (i) how
voltage-dependent subthreshold and spike-dependent
adaptation currents change the neuronal I-O curve as
well as the ISI distribution for different input statistics
and (ii) how these changes compare to those induced by
synaptic inhibition.
Based on a population of adaptive exponential integrate-
and-fire (aEIF) model neurons receiving noisy external
and recurrent synaptic inputs we use the Fokker-Planck
equation to compute spike rates and ISI distributions in
the limit of a large adaptation timescale.
We show that a subthreshold adaptation current or
synaptic inhibition received from independent neurons
(external inhibition) change the neuronal I-O curve sub-
tractively. That is, both mechanisms increase the spike
threshold. On the other hand, a spike-triggered adaptation
current or inhibitory synaptic feedback (recurrent inhibi-
tion) change the I-O curve divisively, i.e., they reduce the
neuronal gain, see Figure 1A. Both types of adaptation
current naturally increase the mean ISI. Surprisingly, they
affect spiking variability in opposite ways. Subthreshold
adaptation leads to an increase while spike-triggered
adaptation causes a decrease of variability, see Figure 1B.
1
Neural Information Processing Group, Berlin Institute of Technology, Berlin,
Germany
Full list of author information is available at the end of the article
Figure 1 Steady-state I-O relationships (A) and ISI distributions (B) for neurons without adaptation (black) and different degrees of
subthreshold (green) or spike-triggered adaptation (magenta), driven by excitatory and inhibitory neurons whose spike times are
generated by Poisson processes.
Ladenbauer et al.BMC Neuroscience 2013, 14(Suppl 1):P299
http://www.biomedcentral.com/1471-2202/14/S1/P299
© 2013 Ladenbauer et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited.
Both types of synaptic inhibition however increase spiking
variability. We simplify the model by neglecting the leak
conductance which allows to analytically derive expres-
sions describing these effects. For validation purposes,
we show that the effective description of subthreshold
and spike-triggered adaptation in the aEIF model corre-
sponds well to the biophysical description of a voltage-
sensitive muscarinic and a calcium-activated potassium
current in a Hodgkin-Huxley type neuron model, respec-
tively. Our results suggest that neuronal adaptation
currents differentially contribute to neuronal threshold
and gain control as well as ISI-based coding schemes.
Acknowledgements
This work was supported by the DFG Collaborative Research Center SFB910.
Author details
1
Neural Information Processing Group, Berlin Institute of Technology, Berlin,
Germany.
2
Bernstein Center for Computational Neuroscience Berlin, Berlin,
Germany.
Published: 8 July 2013
References
1. McCormick DA: Neurotransmitter actions in the thalamus and cerebral
cortex and their role in thalamocortical activity. Progr Neurobiol 1992,
39:337-388.
2. Deemyad T, Kroeger J, Chacron M: Sub and suprathreshold adaptation
currents have opposite effects on frequency tuning. J Physiol 2012,
590:4839-4858.
3. Prescott S, Sejnowski T: Spike-rate coding and spike-time coding are
affected oppositely by different adaptation mechanisms. J Neurosci 2008,
28(50):13649-13661.
4. Herrero JL, Roberts MJ, Delicato LS, Gieselmann MA, Dayan P, Thiele A:
Acetylcholine contributes through muscarinic receptors to attentional
modulation in V1. Nature 2008, 454(28):1110-1114.
doi:10.1186/1471-2202-14-S1-P299
Cite this article as: Ladenbauer et al.: How adaptation currents and
synaptic inhibition change threshold, gain and variability of neuronal
spiking. BMC Neuroscience 2013 14(Suppl 1):P299.
Submit your next manuscript to BioMed Central
and take full advantage of:
• Convenient online submission
• Thorough peer review
• No space constraints or color figure charges
• Immediate publication on acceptance
• Inclusion in PubMed, CAS, Scopus and Google Scholar
• Research which is freely available for redistribution
Submit your manuscript at
www.biomedcentral.com/submit
Ladenbauer et al.BMC Neuroscience 2013, 14(Suppl 1):P299
http://www.biomedcentral.com/1471-2202/14/S1/P299
Page 2 of 2
