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Modeling activity-dependent changes of axonal spike conduction in primary afferent C-nociceptors
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB. Stockholm Brain Institute, Stockholm, Sweden.
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB. Stockholm Brain Institute, Stockholm, Sweden.
Anaesthesiology, Universitaetsmedizin Mannheim, Univ. of Heidelberg.
Inst. of Physiol. and Pathophysiology, Friedrich-Alexander-Uni versität Erlangen-Nürnberg.
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2014 (English)In: Journal of Neurophysiology, ISSN 0022-3077, E-ISSN 1522-1598, Vol. 111, no 9, 1721-1735 p.Article in journal (Refereed) Published
Abstract [en]

Action potential initiation and conduction along peripheral axons is a dynamic process that displays pronounced activity dependence. In patients with neuropathic pain, differences in the modulation of axonal conduction velocity by activity suggest that this property may provide insight into some of the pathomechanisms. To date, direct recordings of axonal membrane potential have been hampered by the small diameter of the fibers. We have therefore adopted an alternative approach to examine the basis of activity-dependent changes in axonal conduction by constructing a comprehensive mathematical model of human cutaneous C-fibers. Our model reproduced axonal spike propagation at a velocity of 0.69 m/s commensurate with recordings from human C-nociceptors. Activity-dependent slowing (ADS) of axonal propagation velocity was adequately simulated by the model. Interestingly, the property most readily associated with ADS was an increase in the concentration of intra-axonal sodium. This affected the driving potential of sodium currents, thereby producing latency changes comparable to those observed for experimental ADS. The model also adequately reproduced post-action potential excitability changes (i.e., recovery cycles) observed in vivo. We performed a series of control experiments replicating blockade of particular ion channels as well as changing temperature and extracellular ion concentrations. In the absence of direct experimental approaches, the model allows specific hypotheses to be formulated regarding the mechanisms underlying activity-dependent changes in C-fiber conduction. Because ADS might functionally act as a negative feedback to limit trains of nociceptor activity, we envisage that identifying its mechanisms may also direct efforts aimed at alleviating neuronal hyperexcitability in pain patients.

Place, publisher, year, edition, pages
2014. Vol. 111, no 9, 1721-1735 p.
Keyword [en]
activity-dependent slowing, recovery cycles, mechano-insensitive nociceptor, computer modeling
National Category
Neurosciences Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:kth:diva-93681DOI: 10.1152/jn.00777.2012ISI: 000335779300002Scopus ID: 2-s2.0-84900796575OAI: oai:DiVA.org:kth-93681DiVA: diva2:517341
Funder
Swedish Research Council, 621-2007-4223
Note

QC 20140602. Updated from manuscript to article in journal.

Available from: 2012-04-23 Created: 2012-04-23 Last updated: 2017-12-07Bibliographically 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.
Series
TRITA-CSC-A, ISSN 1653-5723 ; 2012:02
Keyword
Dendritic excitability, synchronized synaptic input, multicompartment model, epilepsy, axonal excitability, silent C–fibres, Hodgkin–Huxley dynamics, conduction velocity, KA
National Category
Computer Science
Identifiers
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)
Opponent
Supervisors
Note

QC 20102423

Available from: 2012-04-23 Created: 2012-04-18 Last updated: 2014-06-02Bibliographically approved
2. Dendritic and axonal ion channels supporting neuronal integration: From pyramidal neurons to peripheral nociceptors
Open this publication in new window or tab >>Dendritic and axonal ion channels supporting neuronal integration: From pyramidal neurons to peripheral nociceptors
2012 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The nervous system, including the brain, is a complex network with billions of complex neurons. Ion channels mediate the electrical signals that neurons use to integrate input and produce appropriate output, and could thus be thought of as key instruments in the neuronal orchestra. In the field of neuroscience we are not only curious about how our brains work, but also strive to characterize and develop treatments for neural disorders, in which the neuronal harmony is distorted. By modulating ion channel activity (pharmacologically or otherwise) it might be possible to effectively restore neuronal harmony in patients with various types of neural (including channelopathic) disorders. However, this exciting strategy is impeded by the gaps in our understanding of ion channels and neurons, so more research is required. Thus, the aim of this thesis is to improve the understanding of how specific ion channel types contribute to shaping neuronal dynamics, and in particular, neuronal integration, excitability and memory. For this purpose I have used computational modeling, an approach which has recently emerged as an excellent tool for understanding dynamically complex neurophysiological phenomena.

In the first of two projects leading to this thesis, I studied how neurons in the brain, and in particular their dendritic structures, are able to integrate synaptic inputs arriving at low frequencies, in a behaviorally relevant range of ~8 Hz. Based on recent experimental data on synaptic transient receptor potential channels (TRPC), metabotropic glutamate receptor (mGluR) dynamics and glutamate decay times, I developed a novel model of the ion channel current ITRPC, the importance of which is clear but largely neglected due to an insufficient understanding of its activation mechanisms. We found that ITRPC, which is activated both synaptically (via mGluR) and intrinsically (via Ca2+) and has a long decay time constant (τdecay), is better suited than the classical rapidly decaying currents (IAMPA and INMDA) in supporting low-frequency temporal summation. It was further concluded that τdecay varies with stimulus duration and frequency, is linearly dependent on the maximal glutamate concentration, and might require a pair-pulse protocol to be properly assessed.

In a follow-up study I investigated small-amplitude (a few mV) long-lasting (a few seconds) depolarizations in pyramidal neurons of the hippocampal cortex, a brain region important for memory and spatial navigation. In addition to confirming a previous hypothesis that these depolarizations involve an interplay of ITRPC and voltage-gated calcium channels, I showed that they are generated in distal dendrites, are intrinsically stable to weak excitatory and inhibitory synaptic input, and require spatial and temporal summation to occur. I further concluded that the existence of multiple stable states cannot be ruled out, and that, in spite of their small somatic amplitudes, these depolarizations may strongly modulate the probability of action potential generation.

In the second project I studied the axonal mechanisms of unmyelinated peripheral (cutaneous) pain-sensing neurons (referred to as C-fiber nociceptors), which are involved in chronic pain. To my knowledge, the C-fiber model we developed for this purpose is unique in at least three ways, since it is multicompartmental, tuned from human microneurography (in vivo) data, and since it includes several biologically realistic ion channels, Na+/K+ concentration dynamics, a Na-K-pump, morphology and temperature dependence. Based on simulations aimed at elucidating the mechanisms underlying two clinically relevant phenomena, activity-dependent slowing (ADS) and recovery cycles (RC), we found an unexpected support for the involvement of intracellular Na+ in ADS and extracellular K+ in RC. We also found that the two major Na+ channels (NaV1.7 and NaV1.8) have opposite effects on RC. Furthermore, I showed that the differences between mechano-sensitive and mechano-insensitive C-fiber types might reside in differing ion channel densities.

To conclude, the work of this thesis provides key insights into neuronal mechanisms with relevance for memory, pain and neural disorders, and at the same time demonstrates the advantage of using computational modeling as a tool for understanding and discovering fundamental properties of central and peripheral neurons.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2012. x, 126 p.
Series
TRITA-CSC-A, ISSN 1653-5723 ; 2012:09
Keyword
ion channels, computational modeling, simulations, dendrites, axons, TRP, hippocampus, C-fiber nociceptors, pain
National Category
Computer Science
Identifiers
urn:nbn:se:kth:diva-102362 (URN)978-91-7501-475-3 (ISBN)
Public defence
2012-10-09, F3, Lindstedtsv. 26, KTH, Stockholm, 10:00 (English)
Opponent
Supervisors
Funder
Swedish Research Council, 621-2007-3774
Note

QC 20120914

Available from: 2012-09-14 Created: 2012-09-14 Last updated: 2014-06-17Bibliographically approved

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