An analysis of the transitions between down and up states of the cortical slow oscillation under urethane anaesthesia

Wilson, Marcus T.; Barry, Margaret J.; Reynolds, John N. J.; Crump, William P.; Steyn-Ross, D. Alistair; Steyn-Ross, Moira L.; Sleigh, James W.

doi:10.1007/s10867-009-9180-x

Cited by 10 publications

(8 citation statements)

References 36 publications

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“…With the widespread use of MEPs as a measure of efficacy in human TMS studies, the present investigation aimed to explore the effect of anesthetics on MEPs, as a potential complicating variable in mechanistic studies performed on animals. We compared two anesthetics, one that has been previously used to study TMS modulation of MEPs in rodents, xylazine/zoletil ( Hsieh et al, 2015 ), and another that has frequently been used to study the excitability of single neurons and synaptic plasticity at monosynaptic connections, urethane ( Reynolds and Wickens, 2000 ; Clement et al, 2008 ; Parr-Brownlie et al, 2009 ; Schulz et al, 2009 ; Wilson et al, 2010 ; Harris et al, 2014 ). To our knowledge urethane has not been used to study TMS effects on MEPs.…”

Section: Discussionmentioning

confidence: 99%

Differences in Motor Evoked Potentials Induced in Rats by Transcranial Magnetic Stimulation under Two Separate Anesthetics: Implications for Plasticity Studies

Sykes

Matheson

Brownjohn

et al. 2016

Front. Neural Circuits

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Repetitive transcranial magnetic stimulation (rTMS) is primarily used in humans to change the state of corticospinal excitability. To assess the efficacy of different rTMS stimulation protocols, motor evoked potentials (MEPs) are used as a readout due to their non-invasive nature. Stimulation of the motor cortex produces a response in a targeted muscle, and the amplitude of this twitch provides an indirect measure of the current state of the cortex. When applied to the motor cortex, rTMS can alter MEP amplitude, however, results are variable between participants and across studies. In addition, the mechanisms underlying any change and its locus are poorly understood. In order to better understand these effects, MEPs have been investigated in vivo in animal models, primarily in rats. One major difference in protocols between rats and humans is the use of general anesthesia in animal experiments. Anesthetics are known to affect plasticity-like mechanisms and so may contaminate the effects of an rTMS protocol. In the present study, we explored the effect of anesthetic on MEP amplitude, recorded before and after intermittent theta burst stimulation (iTBS), a patterned rTMS protocol with reported facilitatory effects. MEPs were assessed in the brachioradialis muscle of the upper forelimb under two anesthetics: a xylazine/zoletil combination and urethane. We found MEPs could be induced under both anesthetics, with no differences in the resting motor threshold or the average baseline amplitudes. However, MEPs were highly variable between animals under both anesthetics, with the xylazine/zoletil combination showing higher variability and most prominently a rise in amplitude across the baseline recording period. Interestingly, application of iTBS did not facilitate MEP amplitude under either anesthetic condition. Although it is important to underpin human application of TMS with mechanistic examination of effects in animals, caution must be taken when selecting an anesthetic and in interpreting results during prolonged TMS recording.

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Section: Discussionmentioning

confidence: 99%

Differences in Motor Evoked Potentials Induced in Rats by Transcranial Magnetic Stimulation under Two Separate Anesthetics: Implications for Plasticity Studies

Sykes

Matheson

Brownjohn

et al. 2016

Front. Neural Circuits

Self Cite

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“…The data were kindly shared by Melissa Barry and John N. J. Reynolds (University of Otago School of Biomedical Sciences, New Zealand). Details of the corresponding experiment are described by Wilson et al ( 2010 ). In short, neuronal membrane potentials were recorded with a sharp micropipette in the motor cortex of urethane-anesthetised Wistar rats.…”

Section: Methodsmentioning

confidence: 99%

Criteria on Balance, Stability, and Excitability in Cortical Networks for Constraining Computational Models

Maksimov

Diesmann

Albada

2018

Front. Comput. Neurosci.

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During ongoing and Up state activity, cortical circuits manifest a set of dynamical features that are conserved across these states. The present work systematizes these phenomena by three notions: excitability, the ability to sustain activity without external input; balance, precise coordination of excitatory and inhibitory neuronal inputs; and stability, maintenance of activity at a steady level. Slice preparations exhibiting Up states demonstrate that balanced activity can be maintained by small local circuits. While computational models of cortical circuits have included different combinations of excitability, balance, and stability, they have done so without a systematic quantitative comparison with experimental data. Our study provides quantitative criteria for this purpose, by analyzing in-vitro and in-vivo neuronal activity and characterizing the dynamics on the neuronal and population levels. The criteria are defined with a tolerance that allows for differences between experiments, yet are sufficient to capture commonalities between persistently depolarized cortical network states and to help validate computational models of cortex. As test cases for the derived set of criteria, we analyze three widely used models of cortical circuits and find that each model possesses some of the experimentally observed features, but none satisfies all criteria simultaneously, showing that the criteria are able to identify weak spots in computational models. The criteria described here form a starting point for the systematic validation of cortical neuronal network models, which will help improve the reliability of future models, and render them better building blocks for larger models of the brain.

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“…However, while for certain forms of anesthesia it seems plausible that the cortex undergoes a phase transition, it is not clear whether this necessarily holds for natural sleep [39] , [44] . Addressing these issues we present a neural mass model for the sleeping cortex which is extended by sodium dependent potassium current [45] , [46] .…”

Section: Introductionmentioning

confidence: 99%

Characterization of K-Complexes and Slow Wave Activity in a Neural Mass Model

et al. 2014

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NREM sleep is characterized by two hallmarks, namely K-complexes (KCs) during sleep stage N2 and cortical slow oscillations (SOs) during sleep stage N3. While the underlying dynamics on the neuronal level is well known and can be easily measured, the resulting behavior on the macroscopic population level remains unclear. On the basis of an extended neural mass model of the cortex, we suggest a new interpretation of the mechanisms responsible for the generation of KCs and SOs. As the cortex transitions from wake to deep sleep, in our model it approaches an oscillatory regime via a Hopf bifurcation. Importantly, there is a canard phenomenon arising from a homoclinic bifurcation, whose orbit determines the shape of large amplitude SOs. A KC corresponds to a single excursion along the homoclinic orbit, while SOs are noise-driven oscillations around a stable focus. The model generates both time series and spectra that strikingly resemble real electroencephalogram data and points out possible differences between the different stages of natural sleep.

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An analysis of the transitions between down and up states of the cortical slow oscillation under urethane anaesthesia

Cited by 10 publications

References 36 publications

Differences in Motor Evoked Potentials Induced in Rats by Transcranial Magnetic Stimulation under Two Separate Anesthetics: Implications for Plasticity Studies

Differences in Motor Evoked Potentials Induced in Rats by Transcranial Magnetic Stimulation under Two Separate Anesthetics: Implications for Plasticity Studies

Criteria on Balance, Stability, and Excitability in Cortical Networks for Constraining Computational Models

Characterization of K-Complexes and Slow Wave Activity in a Neural Mass Model

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