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Integration of synchronous synaptic input in CA1 pyramidal neuron depends on spatial and temporal distributions of the input
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
Institute of Biophysics, National Research Council.
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.ORCID iD: 0000-0003-0281-9450
2013 (English)In: Hippocampus, ISSN 1050-9631, E-ISSN 1098-1063, Vol. 23, no 1, 87-99 p.Article in journal (Refereed) Published
Abstract [en]

Highly synchronized neural firing has been discussed in relation to learning and memory, for instance sharp-wave activity in hippocampus. We were interested to study how a postsynaptic CA1 pyramidal neuron would integrate input of different levels of synchronicity. In previous work using computational modeling we studied how the integration depends on dendritic conductances. We found that the transient A-type potassium channel KA was able to selectively suppress input of high synchronicity. In recent years, compartmentalization of dendritic integration has been shown. We were therefore interested to study the influence of localization and pattern of synaptic input over the dendritic tree of the CA1 pyramidal neuron. We find that the selective suppression increases when synaptic inputs are placed on oblique dendrites further out from the soma. The suppression also increases along the radial axis from the apical trunk out to the end of oblique dendrites. We also find that the KA channel suppresses the occurrence of dendritic spikes. Moreover, recent studies have shown interaction between synaptic inputs. We therefore studied the influence of apical tuft input on the integration studied above. We find that excitatory input provides a modulatory influence reducing the capacity of KA to suppress synchronized activity, thus facilitating the excitatory drive of oblique dendritic input. Conversely, inhibitory tuft input increases the suppression by KA providing a larger control of oblique depolarizing factors on the CA1 pyramidal neuron in terms of what constitutes the most effective level of synchronicity. Furthermore, we show that the selective suppression studied above depends on the conductance of the KA channel. KA, as several other potassium channels, is modulated by several neuromodulators, for instance acetylcholine and dopamine, both of which have been discussed in relation to learning and memory. We suggest that dendritic conductances and their modulatory systems may be part of the regulation of processing of information, in particular for how network synchronicity affects learning and memory.

Place, publisher, year, edition, pages
2013. Vol. 23, no 1, 87-99 p.
Keyword [en]
A-type potassium channel, Kv 4.2, sharp waves, dendritic spikes
National Category
Neurosciences Bioinformatics (Computational Biology)
URN: urn:nbn:se:kth:diva-93679DOI: 10.1002/hipo.22061ISI: 000312537800010ScopusID: 2-s2.0-84870954627OAI: diva2:517285
Swedish Research Council, 621-2007-4223 13043

QC 20130121

Available from: 2012-04-23 Created: 2012-04-23 Last updated: 2013-01-21Bibliographically approved
In thesis
1. Mechanisms of excitability in the central and peripheral nervous systems: Implications for epilepsy and chronic pain
Open this publication in new window or tab >>Mechanisms of excitability in the central and peripheral nervous systems: Implications for epilepsy and chronic pain
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The work in this thesis concerns mechanisms of excitability of neurons. Specifically, it deals with how neurons respond to input, and how their response is controlled by ion channels and other active components of the neuron. I have studied excitability in two systems of the nervous system, the hippocampus which is responsible for memory and spatial navigation, and the peripheral C–fibre which is responsible for sensing and conducting sensory information to the spinal cord.

Within the work, I have studied the role of excitability mechanisms in normal function and in pathological conditions. For hippocampus the normal function includes changes in excitability linked to learning and memory. However, it also is intimately linked to pathological increases in excitability observed in epilepsy. In C–fibres, excitability controls sensitivity to responses to stimuli. When this response becomes enhanced, this can lead to pain.

I have used computational modelling as a tool for studying hyperexcitability in neurons in the central nervous system in order to address mechanisms of epileptogenesis. Epilepsy is a brain disorder in which a subject has repeated seizures (convulsions) over time. Seizures are characterized by increased and highly synchronized neural activity. Therefore, mechanisms that regulate synchronized neural activity are crucial for the understanding of epileptogenesis. Such mechanisms must differentiate between synchronized and semi synchronized synaptic input. The candidate I propose for such a mechanism is the fast outward current generated by the A-type potassium channel (KA).

Additionally, I have studied the propagation of action potentials in peripheral axons, denoted C–fibres. These C–fibres mediate information about harmful peripheral stimuli from limbs and organs to the central nervous system and are thereby linked to pathological pain. If a C–fibre is activated repeatedly, the excitability is altered and the mechanisms for this alteration are unknown. By computational modelling, I have proposed mechanisms which can explain this alteration in excitability.

In summary, in my work I have studied roles of particular ion channels in excitability related to functions in the nervous system. Using computational modelling, I have been able to relate specific properties of ion channels to functions of the nervous system such as sensing and learning, and in particular studied the implications of mechanisms of excitability changes in diseases.


Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2012. xii, 100 p.
TRITA-CSC-A, ISSN 1653-5723 ; 2012:02
Dendritic excitability, synchronized synaptic input, multicompartment model, epilepsy, axonal excitability, silent C–fibres, Hodgkin–Huxley dynamics, conduction velocity, KA
National Category
Computer Science
urn:nbn:se:kth:diva-93496 (URN)978-91-7501-307-7 (ISBN)
Public defence
2012-05-08, F3, Lindstedtsvägen 26, KTH, Stockholm, 10:00 (English)

QC 20102423

Available from: 2012-04-23 Created: 2012-04-18 Last updated: 2014-06-02Bibliographically approved

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