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Low-frequency summation of synaptically activated transient receptor potential channel-mediated depolarizations
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.ORCID iD: 0000-0003-0281-9450
2011 (English)In: European Journal of Neuroscience, ISSN 0953-816X, E-ISSN 1460-9568, Vol. 34, no 4, 578-593 p.Article in journal (Refereed) Published
Abstract [en]

Neurons sum their input by spatial and temporal integration. Temporally, presynaptic firing rates are converted to dendritic membrane depolarizations by postsynaptic receptors and ion channels. In several regions of the brain, including higher association areas, the majority of firing rates are low. For rates below 20 Hz, the ionotropic receptors alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor and N-methyl-d-aspartate (NMDA) receptor will not produce effective temporal summation. We hypothesized that depolarization mediated by transient receptor potential (TRP) channels activated by metabotropic glutamate receptors would be more effective, owing to their slow kinetics. On the basis of voltage-clamp and current-clamp recordings from a rat slice preparation, we constructed a computational model of the TRP channel and its intracellular activation pathway, including the metabotropic glutamate receptor. We show that synaptic input frequencies down to 3-4 Hz and inputs consisting of as few as three to five pulses can be effectively summed. We further show that the time constant of integration increases with increasing stimulation frequency and duration. We suggest that the temporal summation characteristics of TRP channels may be important at distal dendritic arbors, where spatial summation is limited by the number of concurrently active synapses. It may be particularly important in regions characterized by low and irregular rates.

Place, publisher, year, edition, pages
2011. Vol. 34, no 4, 578-593 p.
Keyword [en]
computational model, dendritic integration, entorhinal cortex, integration time constant, mGluR
National Category
Neurosciences Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:kth:diva-38955DOI: 10.1111/j.1460-9568.2011.07791.xISI: 000293907400007PubMedID: 21777305Scopus ID: 2-s2.0-80051673126OAI: oai:DiVA.org:kth-38955DiVA: diva2:438919
Funder
Swedish Research Council, 621-2007-3774
Available from: 2011-09-06 Created: 2011-09-05 Last updated: 2017-12-08Bibliographically approved
In thesis
1. Beyond AMPA and NMDA: Slow synaptic mGlu/TRPC currents: Implications for dendritic integration
Open this publication in new window or tab >>Beyond AMPA and NMDA: Slow synaptic mGlu/TRPC currents: Implications for dendritic integration
2010 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

In order to understand how the brain functions, under normal as well as pathological conditions, it is important to study the mechanisms underlying information integration. Depending on the nature of an input arriving at a synapse, different strategies may be used by the neuron to integrate and respond to the input. Naturally, if a short train of high-frequency synaptic input arrives, it may be beneficial for the neuron to be equipped with a fast mechanism that is highly sensitive to inputs on a short time scale. If, on the contrary, inputs arriving with low frequency are to be processed, it may be necessary for the neuron to possess slow mechanisms of integration. For example, in certain working memory tasks (e. g. delay-match-to-sample), sensory inputs may arrive separated by silent intervals in the range of seconds, and the subject should respond if the current input is identical to the preceeding input. It has been suggested that single neurons, due to intrinsic mechanisms outlasting the duration of input, may be able to perform such calculations. In this work, I have studied a mechanism thought to be particularly important in supporting the integration of low-frequency synaptic inputs. It is mediated by a cascade of events that starts with activation of group I metabotropic glutamate receptors (mGlu1/5), and ends with a membrane depolarization caused by a current that is mediated by canonical transient receptor potential (TRPC) ion channels. This current, denoted ITRPC, is the focus of this thesis.

A specific objective of this thesis is to study the role of ITRPC in the integration of synaptic inputs arriving at a low frequency, < 10 Hz. Our hypothesis is that, in contrast to the well-studied, rapidly decaying AMPA and NMDA currents, ITRPC is well-suited for supporting temporal summation of such synaptic input. The reason for choosing this range of frequencies is that neurons often communicate with signals (spikes) around 8 Hz, as shown by single-unit recordings in behaving animals. This is true for several regions of the brain, including the entorhinal cortex (EC) which is known to play a key role in producing working memory function and enabling long-term memory formation in the hippocampus.

Although there is strong evidence suggesting that ITRPC is important for neuronal communication, I have not encountered a systematic study of how this current contributes to synaptic integration. Since it is difficult to directly measure the electrical activity in dendritic branches using experimental techniques, I use computational modeling for this purpose. I implemented the components necessary for studying ITRPC, including a detailed model of extrasynaptic glutamate concentration, mGlu1/5 dynamics and the TRPC channel itself. I tuned the model to replicate electrophysiological in vitro data from pyramidal neurons of the rodent EC, provided by our experimental collaborator. Since we were interested in the role of ITRPC in temporal summation, a specific aim was to study how its decay time constant (τdecay) is affected by synaptic stimulus parameters.

The hypothesis described above is supported by our simulation results, as we show that synaptic inputs arriving at frequencies as low as 3 - 4 Hz can be effectively summed. We also show that τdecay increases with increasing stimulus duration and frequency, and that it is linearly dependent on the maximal glutamate concentration. Under some circumstances it was problematic to directly measure τdecay, and we then used a pair-pulse paradigm to get an indirect estimate of τdecay.

I am not aware of any computational model work taking into account the synaptically evoked ITRPC current, prior to the current study, and believe that it is the first of its kind. We suggest that ITRPC is important for slow synaptic integration, not only in the EC, but in several cortical and subcortical regions that contain mGlu1/5 and TRPC subunits, such as the prefrontal cortex. I will argue that this is further supported by studies using pharmacological blockers as well as studies on genetically modified animals.

Place, publisher, year, edition, pages
Stockholm: KTH, 2010. viii, 67 p.
Series
Trita-CSC-A, ISSN 1653-5723 ; 2010:13
Keyword
transient receptor potential, TRP, metabotropic glutamate receptor, mGlu1/5, dendritic integration, synaptic activation, temporal summation, low-frequency, entorhinal cortex, mathematical model, computational neuroscience
National Category
Computer Science
Identifiers
urn:nbn:se:kth:diva-24833 (URN)978-91-7415-745-1 (ISBN)
Presentation
2010-10-29, RB35, Roslagstullsbacken 35, Stockholm, AlbaNova, 13:00
Opponent
Supervisors
Note
QC 20101005Available from: 2010-10-05 Created: 2010-09-27 Last updated: 2011-11-30Bibliographically 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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