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Abstract

Background

Spreading depression (SD) is the electrophysiological substrate of migraine aura and a potential trigger for headache. Since its discovery by Leão in 1944, SD has transformed from being viewed as an epiphenomenon into a therapeutic target relevant in the pathophysiology of migraine and brain injury.

Aim

Despite decades of research, the underpinnings of SD are still poorly understood, hampering our efforts to selectively block its initiation and spread. Experimental models have nevertheless been useful to measure the likelihood of SD occurrence (i.e. SD susceptibility) and characterize genetic, physiological and pharmacological modulation of SD in search of potential therapies, such as in migraine prophylaxis and stroke. Here, I review experimental SD susceptibility endpoints and surrogates, and minimum essential model requirements to improve their utility in drug screening.

Conclusion

A critical reappraisal of strengths and caveats of experimental models of SD susceptibility is needed to set standards and improve data quality, interpretation and reconciliation.

Keywords

Spreading depression migraine aura animal models

Introduction

Spreading depression (SD) is an intense neuronal and glial depolarization wave that slowly propagates in brain tissue (∼3 mm/min) by way of gray matter contiguity. The near-complete loss of membrane potential is a result of massive transmembrane ionic and water shifts, including a K⁺ and glutamate efflux, and Na⁺, Ca²⁺ and water influx, which last up to a minute and does not lead to injury in otherwise normal brain tissue. It is believed that the rise in extracellular K⁺ and glutamate act as chemical signals diffusing to and depolarizing adjacent cells, and in this way the depolarization slowly spreads regardless of functional or vascular divisions. For the released K⁺ and glutamate to reach the critical depolarization threshold of adjacent cells, high neuronal and synaptic density and low extracellular space volume are required; therefore, white matter is characteristically resistant to SD. All these ionic and water shifts create a signature extracellular negative slow potential shift (aka DC shift) accompanied by suppression of action potentials and synaptic activity (Figure 1). As a result, electrocorticogram (ECoG) is depressed, hence the historical term “spreading depression” originally coined by Leão (1**).

Figure 1.

Cortical spreading depression (SD) triggered by a suprathreshold stimulus delivered on to the frontal cortex is detected by a glass micropipette a few mm away in the parietal cortex after a latency accounting for its slow propagation speed. Note the large negative slow (DC) potential shift that lasts approximately 30 sec (upper tracing) and the concurrent electrocorticogram (ECoG) suppression (lower tracing) that outlasts the DC shift by several minutes. The DC shift accompanied by ECoG suppression is the most reliable electrophysiological signature of SD. Tracings are from a rat under isoflurane and nitrous oxide anesthesia. Vertical scale 20 mV DC, 0.4 mV ECoG; horizontal scale 1 min.

Since the discovery of SD decades ago, similarities between the electrophysiological properties of SD and the neurological signs and symptoms during migraine aura suggested a causative link between the two (2 –4). A large body of evidence now supports the SD theory of migraine (5). Moreover, experimental evidence also suggests that SD can trigger headache (6 –10**,11). Although whether an asymptomatic SD triggers migraine headache without a perceived aura is still debated, suppression of SD susceptibility by migraine prophylactic drugs as a class effect (12 –14**,15 –18) supported this notion since these drugs have been equally efficacious in migraine with or without a perceived aura. Therefore, SD is now considered a potential therapeutic target in migraine, and experimental models of SD susceptibility are increasingly being used to screen for migraine drug candidates. A range of experimental models of SD has been developed, although the sensitivity and specificity and the predictive value of each model have not been systematically investigated, and a consensus is still lacking.

In vitro vs. in vivo models

In vitro models, such as isolated retina and brain slices, have been used in the past to study the effects of various pharmacological agents on SD properties. These models bypass the blood-brain barrier and eliminate hemodynamic, pharmacokinetic, anesthesia-related and systemic physiological factors. However, tissue oxygenation and metabolism differ from the in vivo state because of the absence of blood flow (19,20), exposure to hypoxia and trauma during experimental preparation may confound the results, and it is difficult to judge the clinically relevant drug concentrations when directly superfused in vitro. Therefore, convenience of the relatively high-throughput in vitro drug screening is offset by difficulties in extrapolating the in vitro results to in vivo efficacy.

In vivo models have been for the most part limited to cerebral cortex because of ease of access. Although most studies have been in rodents, a wide variety of species from pigeons to cats and monkeys have been used (21,22). There is a fair degree of interspecies variability in SD susceptibility. In general, the larger the brain is, the lower the susceptibility (e.g. mouse vs. rat). In addition, gyrencephalic species (e.g. cats) are less susceptible than lissencephalic species (e.g. rodents). Species differences in SD susceptibility, and their determinants, have not been systematically studied. Although increasing astrocyte/neuron ratios in higher species have frequently been cited as the cause (23,24), it is unlikely to be the only determinant.

Methods to trigger SD

SD is triggered when a sufficiently intense depolarizing stimulus raises extracellular [K⁺] above a threshold in a minimum critical volume of tissue, estimated to be approximately 12 mM and 1 mm³, respectively, in rodent brain (25 –27). The depolarizing stimulus is most commonly electrical, chemical or mechanical.

Electrical stimulation is one of the most direct methods to assess SD susceptibility (14**,28,29). A single square pulse of stepwise escalating cathodal charge is applied at regular intervals (e.g. every 4–5 minutes) until an SD is triggered (Figure 2). The product of stimulus current (ampere) and duration (seconds) that triggers an SD is then taken as the charge intensity threshold (coulomb). High-frequency train stimulation of increasing intensity or duration is an alternative approach. The absolute threshold values in any experimental setting critically depend on methodological details. Electrode properties and electrode-tissue contact determine the stimulus geometry, which heavily influences the charge intensity required to trigger an SD. Stimulus geometry is best controlled by a cortical cup electrode (26); however, this is not always available or practical. Instead, both unipolar and concentric or parallel bipolar electrodes can be used. We favor the latter since stimulus polarity can be alternated to minimize oxidation. In all cases, slight differences in tip separation or insulation between two electrodes, or changes in the same electrode due to wear and tear over time, can result in different absolute threshold values. Therefore, it is important not to rely on historical controls when studying modulation of electrical threshold. Electrical threshold yields categorical (i.e. non-parametric) data, and often shows higher variability compared to chemical depolarizing agents because of irregularities at the electrode-tissue contact (e.g. bleeding or drying).

Figure 2.

Direct electrical stimulation of cortex with stepwise escalating charge intensities (single square pulses of alternating polarity using a bipolar electrode in this example) triggers a spreading depression (SD) when the threshold is reached. The stimulus intensity steps depend on the electrode and the species, and can be adjusted according to the hypothesis being tested; if testing a drug or mutation that significantly lowers the threshold, it would be important to start at a low stimulus intensity with small step increases. Tracing is from a representative rat under isoflurane and nitrous oxide anesthesia. Vertical scale bar 10 mV; horizontal scale bar 2 min.

The most common chemical depolarizing agent used to determine SD susceptibility is concentrated KCl solution (often 50 mM or higher), although glutamate receptor agonists (e.g. N-methyl-D-aspartate (NMDA)), Ca²⁺ channel openers or ionophores (e.g. Bay K8644), and Na⁺ channel activators (e.g. aconitine) can all trigger SD. Depolarizing agents can be applied topically (14**,30), or intraparenchymally using a pneumatic injection or microdialysis system (31,32). To determine the SD threshold, one can then escalate the concentration of the depolarizing agent (Figure 3), or the volume injected, in a stepwise manner (33,34).

Figure 3.

Topical application of stepwise increasing concentrations of KCl solution triggers a spreading depression (SD) at a threshold concentration of 40 mM. As with electrical stimulation, the KCl concentration steps can be tailored to the hypothesis; for example, when studying a drug or mutation that is anticipated to significantly lower the threshold, testing should start at a lower concentration with smaller step increases. Tracing is from a representative mouse under isoflurane and nitrous oxide anesthesia. Vertical scale bar 10 mV; horizontal scale bar 1 min.

Alternatively, a constant suprathreshold concentration (e.g. 1 M KCl) can be applied continuously to trigger repetitive SDs (Figure 4) and determine their frequency (14**,30,35). An important potential caveat of SD frequency endpoint is the absolute and relative refractory periods during which a subsequent SD cannot be triggered (36). Importantly, longer SD durations are associated with prolonged refractory periods and lower SD frequencies, which may be misinterpreted as lower susceptibility. In such cases, the total cumulative SD duration (e.g. per hour) may be an alternative endpoint. Because SD frequency yields continuous data and is less prone to cortical surface irregularities, it tends to be statistically more powerful compared to electrical threshold. Both KCl concentration threshold and KCl-induced SD frequency critically depend on the cranial window diameter and the presence of dura. Therefore, these parameters must be identical across animals and experimental groups, different experimenters, and if possible, different labs.

Figure 4.

Continuous topical KCl application on occipital cortex (horizontal line on top) triggers repetitive spreading depression (SD) waves recorded from the parietal cortex. Occasional small-amplitude SDs are included in the count if they are larger than 5 mV (arrowhead). Note the suppression and recovery of the electrocorticogram (ECoG) after each SD (arrows), which often helps differentiate electrical noise from true SDs when the latter is very small (dot). Tracing is from a representative rat under isoflurane and nitrous oxide anesthesia. Vertical scale bar 10 mV; horizontal scale bar 5 min.

Mechanical stimulation has also been used to assess SD susceptibility. However, it is difficult to titrate to determine a threshold. Therefore, SD susceptibility is measured by how often a single mechanical stimulus triggers SD, i.e. an all or none response (37). Repetitive assessment can be problematic because of poor reproducibility of the stimulus and cumulative traumatic injury. Furthermore, mechanically induced SD appears to have a different pharmacological profile compared to chemical or electrical SD induction (38,39). Other methods to trigger SD include high-frequency afferent pathway stimulation and focal cerebral ischemia (40), but these are not practical for high-throughput drug screening.

Methods to detect SD

Electrophysiologically, the characteristic extracellular negative slow potential shift is the gold standard to detect SD. This is often briefly preceded by a burst of neuronal firing that can be detected by single unit recordings, followed by a longer lasting suppression of neuronal firing and ECoG activity. Although this pattern of single unit activity can be used as a surrogate for the slow potential shift (37 –39), it is neither more sensitive nor more specific than the latter, does not directly inform about the depolarization duration or amplitude, and cannot be used if the test drug has a direct inhibitory effect on neuronal firing (e.g. tetrodotoxin).

An alternative method to detect SD in vivo is diffusion-weighted magnetic resonance imaging (MRI) (41). The advantages of being non-invasive and three dimensional are offset by relatively low spatial and temporal resolution. Therefore, MRI may be superior to traditional electrophysiological methods only in larger gyrencephalic species and low SD repetition rates. SD is also associated with characteristic optical intrinsic signal transients (42). These are caused by changes in light absorption and scattering properties of the tissue due to transmembrane ionic and water shifts, as well as changes in tissue hemoglobin concentration. Alternatively, one can also monitor the large amplitude blood flow transients to detect SD (38,43). These are complementary surrogates, but should not replace the slow potential shift as the standard method to detect SD.

Relevant SD attributes

SD susceptibility is defined as the likelihood of the brain tissue to develop and sustain SD. There are various experimental models and approaches that have been used by different labs to assess SD susceptibility. Physiological processes interrogated by each model, and the translational value of their readouts, have not been established. Of course, each model has strengths and pitfalls, and agreement of results among models remains to be established.

Arguably the most relevant measure of SD susceptibility is the threshold intensity of electrical charge or threshold concentration or volume of the depolarizing agent (e.g. KCl) that triggers an SD, as described above. The threshold topical electrical stimulation intensity and the threshold KCl concentration for SD induction show excellent concordance (34). Interestingly, continuous topical KCl-induced SD frequency has also showed complete concordance with electrical SD threshold when studied in the same animal in our hands (14**,16,17,28). The relationship is inverse, such that lower SD thresholds yield higher SD frequencies and vice versa. Importantly, SD frequency has a theoretical ceiling determined by the SD duration and the absolute refractory period during which a subsequent SD cannot be initiated, which is estimated to be two to three minutes. Therefore, one cannot trigger more than 20–30 SDs in one hour regardless of the intensity of stimulation, a ceiling that we have observed in highly susceptible mutant mouse strains (30).

Other measures of the slow potential shift, such as its propagation speed, duration, and amplitude, may also be relevant, although how these measures relate to SD susceptibility and their predictive value have not been studied. In our own pooled data from 87 controlled cohorts with genetic, physiological or pharmacological manipulation (n = 766 mice and rats) published between 2000 and 2012 (14**,16,17,28,30,34,35,44,45), there was strong correspondence between susceptibility and propagation speed (Table 1). Propagation speed had modest sensitivity (67%) and specificity (76%) in predicting a change in SD susceptibility, with positive and negative predictive values of 84% and 56%, respectively (κ = 0.75; 95% confidence interval (CI) = 0.62–0.89). In contrast, SD duration and amplitude did not show a consistent relationship to SD susceptibility.

Table 1.

The relationship between SD susceptibility and other SD attributes.

(% of all cohorts)	SD speed			SD duration			SD amplitude
SD susceptibility	Increased	Unchanged	Decreased	Increased	Unchanged	Decreased	Increased	Unchanged	Decreased
Increased	27	8	4	31	35
Unchanged	4	27	4	4	31	35
Decreased	13	17	3	21	6	30
κ	0.75 (0.84)			0.17			0.00

SD: spreading depression.

Numbers indicate percentage distribution of susceptibility outcome (threshold and/or frequency) vs. speed, duration and amplitude outcomes when measured in the same cohort, categorized based on statistically significant increase or decrease, or no change. Sensitivity, specificity, and positive and negative predictive values of SD speed to predict SD susceptibility were calculated from true positives (attribute changes in the same direction as susceptibility), true negatives (neither susceptibility nor attribute shows a change), false negatives (attribute fails to show a change when susceptibility is changed), and false positives (attribute shows a change when susceptibility is unchanged, or attribute shows a change in the direction opposite to the change in susceptibility). Kappa (κ)statistic was calculated with quadratic weighting. The corrected κ value as proportion of maximum possible (given the observed marginal frequencies) is also provided in parentheses. κ = 1 is the theoretical maximum, while κ > 0.75 is regarded as excellent agreement.

Although based on these data, propagation speed may be an acceptable surrogate to detect a change in SD susceptibility, its clinical relevance is not clear. Moreover, there are potential caveats associated with these surrogates. For example, the propagation speed as well as the duration decrease with each successive SD to reach a plateau as much as 25% lower than the initial values after a few SDs. Therefore, care should be taken to not trigger SDs inadvertently during cranial surgery as these will make subsequent SD speeds and durations appear lower than normal. We recommend monitoring accidental SD occurrence, for example, by non-invasive laser Doppler flowmetry, during experimental preparation, particularly in rodents where SD susceptibility is inherently high.

When monitoring SD occurrence for threshold determination, one should keep in mind that SDs can fail to propagate, especially when SD susceptibility is dramatically reduced (34). Because of this, the rate of SD detection can vary inversely with the distance between the recording and stimulation sites. To minimize this confounder, we adopted the use of two recording sites, one sufficiently close to the stimulation site (but not too close to be directly depolarized during stimulation, typically a couple of mm), and one farther away. This arrangement allows the detection of most if not all SDs, as well as the calculation of propagation failure rate between the two recording sites.

Recommended quality measures

In vivo vs. in vitro testing

In general, in vitro models (e.g. isolated retina) may provide a high-throughput system for initial SD susceptibility testing (46,47). However, especially in drug screening, promising hits must then be fully characterized in vivo upon systemic administration, preferably in more than one species and both sexes. Although testing in a gyrencephalic species may be intuitive, there is yet no evidence to suggest that efficacy in gyrencephalic species better predicts efficacy in human compared to rodent models. Migraine is a genetic disease, and the recent development of transgenic mouse models expressing human migraine mutations (28,30,45,48 –50) provides an excellent opportunity to test drug efficacy in a genetically susceptible population.

Anesthesia

Anesthesia modulates SD susceptibility (35,51 –57). Inhalational anesthetics such as isoflurane and nitrous oxide, and particularly the NMDA receptor blocker and dissociative anesthetic ketamine, suppress SD induction and hinder propagation. Propofol was recently reported to suppress SD as well (58), although this remains to be confirmed. In our experience, barbiturates, urethane and α-chloralose do not significantly inhibit SD, and should be the first choice when feasible. However, an additional consideration is the ease with which anesthesia can be induced and maintained over time while preserving systemic physiology (e.g. arterial blood gas and pressure). Deep anesthesia often results in hypotension, which is a potential confounder when determining SD frequency (see below). Significant respiratory depression necessitates mechanical ventilation, a particularly challenging task in mice. These side effects are common with barbiturates, urethane and α-chloralose. In general, an anesthetic that acts on the same target as the drug to be tested should be avoided (e.g. barbiturate anesthesia when testing a drug that acts on γ-amino butyric acid (GABA)_A receptors, or ketamine when testing the efficacy of an NMDA receptor blocker). Anesthesia must be carefully tailored for each study in order not to confound the results and diminish the sensitivity of the employed assays. The convenience of anesthesia induction and maintenance by a given anesthetic should be weighed against its direct impact on SD susceptibility, and possible interactions between the anesthetic and the modulator (e.g. mutation or drug) to be tested.

Systemic physiology

It is imperative that systemic physiology be monitored, and when necessary, controlled (e.g. mechanical ventilation) in experimental models of SD susceptibility. Arterial blood pressure is inversely related to SD duration (59,60). Hypotension, even if mild, prolongs SD duration, which in turn prolongs the absolute refractory period. As a result, SD frequency during continuous topical KCl stimulation will be reduced. Hence, a drug that consistently reduces blood pressures may yield lower SD frequencies, and vice versa (6,61). Whether blood pressure also directly alters SD threshold has not been tested. Arterial blood gas and pH are also expected to influence SD susceptibility, but the relationship is less straightforward and has not been well investigated. Nevertheless, maintaining these values within normal physiological ranges is good practice. We perform endotracheal intubation and mechanical ventilation routinely in rats and when necessary in mice (e.g. barbiturate anesthesia), as the latter species is more fragile and tends to get hypotensive with prolonged anesthesia and mechanical ventilation. Of note, certain mouse strains are more resilient and can maintain their blood pressure for longer periods of anesthesia and ventilation. Blood glucose is also an important factor. Hyperglycemia inhibits SD susceptibility (62 –65), whereas hypoglycemia prolongs SD durations (64). Therefore, blood glucose measurements further improve the consistency, particularly when genetic, physiological or pharmacological interventions are anticipated to alter this parameter. Overnight fasting generally stabilizes the systemic physiology and ameliorates hyperglycemia during surgery and subsequent interventions, but also tends to enhance SD susceptibility directly. Lastly, body temperature must also be regulated under anesthesia.

Surgical preparation and maintenance

Surgical preparation and maintenance of the craniotomy are also critical for reliable and consistent results and intra- and interobserver reproducibility. Of course, cortical injury due to trauma or heat during craniotomy, and bleeding or drying can all affect SD susceptibility. The cortex must be kept moist by artificial cerebrospinal fluid (CSF) or physiologic saline to maintain isotonicity during the experiments. Dura must be removed prior to electrical and chemical stimulation in rats and larger animals, but can be left intact in mice, as it is sufficiently thin and difficult to remove in an atraumatic fashion.

SD susceptibility

The most direct and relevant SD attribute is susceptibility, monitored using intraparenchymal extracellular microelectrode recordings of slow potential shift combined with ECoG activity. We prefer to determine the electrical threshold on one hemisphere, and KCl-induced SD frequency on the other hemisphere of the same animal; these two methods are non-overlapping but complementary measures of SD susceptibility and correlate well. We also routinely measure SD speed, duration and amplitude, and use them to obtain additional physiological insight.

Pharmacokinetic factors

Careful consideration of pharmacokinetic factors (e.g. absorption and elimination rates and routes, plasma and brain levels), seeking a dose-response relationship, testing the efficacy of repeated or chronic dosing paradigms in addition to a single dose, and including a positive control (e.g. a drug known to produce the sought effect) among the cohorts, all minimize the type II error.

Conduct of research

Last but not least, responsible conduct of research must be ensured by single or double blinding, and independent confirmation of data in a second laboratory. Inclusion of a negative control (e.g. a drug known to be ineffective) helps minimize type I error. In this context, Animal Research: Reporting of In Vivo Experiments (ARRIVE) guidelines for reporting animal research are worth adopting universally (66).

Future directions and unmet needs

As SD is increasingly recognized as a potential therapeutic target not only in migraine but also in stroke and other brain injury states, research into the determinants and modulators of SD susceptibility (Figure 5) has been gaining momentum (67). As more experimental data on SD susceptibility become available, its predictive and translational therapeutic value will be better defined. In order to ensure efficient progress in the field, there is a need for an in-depth and timely discussion of relevant models and attributes toward a consensus standardization of the experimental approaches used in different labs.

Figure 5.

There are numerous modulators of spreading depression (SD) susceptibility, intrinsic or environmental, some of which are modifiable. Checkmarks indicate existing supportive evidence experimentally or clinically. A detailed discussion of pharmacological targets can be found in Ayata (13).

Footnotes

Funding

This work was funded in part by the United States National Institutes of Health (NIH) (NS061505) and the Andrew David Heitman Neuroendovascular Research Fund from the Andrew David Heitman Foundation.

Conflict of interest

None declared.

References

Leão

AAP

. Spreading depression of activity in cerebral cortex. J Neurophysiol 1944; 7: 359–390. **First report defining spreading depression and its basic features .

Leão

AAP

Morison

. Propagation of spreading cortical depression. J Neurophysiol 1945; 8: 33–45.

Milner

. Note on a possible correspondence between the scotomas of migraine and spreading depression of Leão. Electroencephalogr Clin Neurophysiol 1958; 10: 705–705.

Lauritzen

. On the possible relation of spreading cortical depression to classical migraine. Cephalalgia 1985; 5(Suppl 2): 47–51.

Ayata

. Cortical spreading depression triggers migraine attack: Pro. Headache 2010; 50: 725–730.

Moskowitz

Nozaki

Kraig

. Neocortical spreading depression provokes the expression of c-fos protein-like immunoreactivity within trigeminal nucleus caudalis via trigeminovascular mechanisms. J Neurosci 1993; 13: 1167–1177.

Kunkler

Kraig

. Hippocampal spreading depression bilaterally activates the caudal trigeminal nucleus in rodents. Hippocampus 2003; 13: 835–844.

Buzzi

Bonamini

Moskowitz

. Neurogenic model of migraine. Cephalalgia 1995; 15: 277–280.

Bolay

Reuter

Dunn

. Intrinsic brain activity triggers trigeminal meningeal afferents in a migraine model. Nat Med 2002; 8: 136–142.

10.

Zhang

Levy

Kainz

. Activation of central trigeminovascular neurons by cortical spreading depression. Ann Neurol 2011; 69: 855–865. **Direct demonstration using electrophysiological recordings from nucleus caudalis that cortical spreading depression is capable of activating downstream pain pathways .

11.

Zhang

Levy

Noseda

. Activation of meningeal nociceptors by cortical spreading depression: Implications for migraine with aura. J Neurosci 2010; 30: 8807–8814.

12.

Eikermann-Haerter

Ayata

. Cortical spreading depression and migraine. Curr Neurol Neurosci Rep 2010; 10: 167–173.

13.

Ayata

. Spreading depression: From serendipity to targeted therapy in migraine prophylaxis. Cephalalgia 2009; 29: 1095–1114.

14.

Ayata

Jin

Kudo

. Suppression of cortical spreading depression in migraine prophylaxis. Ann Neurol 2006; 59: 652–661. **First comprehensive investigation of the impact of several migraine prophylactic drugs on spreading depression susceptibility as a common final mechanism of action .

15.

Bogdanov

Multon

Chauvel

. Migraine preventive drugs differentially affect cortical spreading depression in rat. Neurobiol Dis 2011; 41: 430–435.

16.

Hoffmann

Dileköz

Kudo

. Oxcarbazepine does not suppress cortical spreading depression. Cephalalgia 2011; 31: 537–542.

17.

Hoffmann

Dileköz

Kudo

. Gabapentin suppresses cortical spreading depression susceptibility. J Cereb Blood Flow Metab 2010; 30: 1588–1592.

18.

Unekawa

Tomita

Toriumi

. Suppressive effect of chronic peroral topiramate on potassium-induced cortical spreading depression in rats. Cephalalgia 2012; 32: 518–527.

19.

Galeffi

Somjen

Foster

. Simultaneous monitoring of tissue PO(2) and NADH fluorescence during synaptic stimulation and spreading depression reveals a transient dissociation between oxygen utilization and mitochondrial redox state in rat hippocampal slices. J Cereb Blood Flow Metab 2011; 31: 626–639.

20.

Turner

Foster

Galeffi

. Differences in O(2) availability resolve the apparent discrepancies in metabolic intrinsic optical signals in vivo and in vitro. Trends Neurosci 2007; 30: 390–398.

21.

Shima

Fifkova

Bures

. Limits of spreading depression in pigeon striatum. J Comp Neurol 1963; 121: 485–492.

22.

Van Harreveld

Stamm

Christensen

. Spreading depression in rabbit, cat and monkey. Am J Physiol 1956; 184: 312–320.

23.

Tower

Young

. The activities of butyrylcholinesterase and carbonic anhydrase, the rate of anaerobic glycolysis, and the question of a constant density of glial cells in cerebral cortices of various mammalian species from mouse to whale. J Neurochem 1973; 20: 269–278.

24.

Gardner-Medwin

. Possible roles of vertebrate neuroglia in potassium dynamics, spreading depression and migraine. J Exp Biol 1981; 95: 111–127.

25.

Matsuura

Bures

. The minimum volume of depolarized neural tissue required for triggering cortical spreading depression in rat. Exp Brain Res 1971; 12: 238–249.

26.

Reid

Marrannes

Wauquier

. Spreading depression and central nervous system pharmacology. J Pharmacol Methods 1988; 19: 1–21.

27.

Nicholson

Kraig

The behaviour of extracellular ions during spreading depression. In: Zeuthen

(ed.) The application of ion-selective microelectrodes, Amsterdam: Elsevier, 1981, pp. 217–238.

28.

Eikermann-Haerter

Yuzawa

Dileköz

. Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy syndrome mutations increase susceptibility to spreading depression. Ann Neurol 2011; 69: 413–418.

29.

Reid

Marrannes

De Prins

. Strength-duration properties of cathodal pulses eliciting spreading depression in rat cerebral cortex. Brain Res 1987; 404: 361–364.

30.

Eikermann-Haerter

Dileköz

Kudo

. Genetic and hormonal factors modulate spreading depression and transient hemiparesis in mouse models of familial hemiplegic migraine type 1. J Clin Invest 2009; 119: 99–109.

31.

Wang

Obrenovitch

Urenjak

. Effects of the nitric oxide donor, DEA/NO on cortical spreading depression. Neuropharmacology 2003; 44: 949–957.

32.

Obrenovitch

Urenjak

Zilkha

. Intracerebral microdialysis combined with recording of extracellular field potential: A novel method for investigation of depolarizing drugs in vivo. Br J Pharmacol 1994; 113: 1295–1302.

33.

Brennan

Romero Reyes

López Valdés

. Reduced threshold for cortical spreading depression in female mice. Ann Neurol 2007; 61: 603–606.

34.

Ayata

Shimizu-Sasamata

. Impaired neurotransmitter release and elevated threshold for cortical spreading depression in mice with mutations in the alpha1A subunit of P/Q type calcium channels. Neuroscience 2000; 95: 639–645.

35.

Kudo

Nozari

Moskowitz

. The impact of anesthetics and hyperoxia on cortical spreading depression. Exp Neurol 2008; 212: 201–206.

36.

Bures

Buresova

Krivanek

. The mechanism and applications of Leao's spreading depression of electroencephalographic activity, New York: Academic Press, 1974.

37.

Akerman

Goadsby

. Topiramate inhibits cortical spreading depression in rat and cat: Impact in migraine aura. Neuroreport 2005; 16: 1383–1387.

38.

Akerman

Holland

Goadsby

. Mechanically-induced cortical spreading depression associated regional cerebral blood flow changes are blocked by Na+ ion channel blockade. Brain Res 2008; 1229: 27–36.

39.

Holland

Akerman

Goadsby

. Cortical spreading depression-associated cerebral blood flow changes induced by mechanical stimulation are modulated by AMPA and GABA receptors. Cephalalgia 2010; 30: 519–527.

40.

Nozari

Dileköz

Sukhotinsky

. Microemboli may link spreading depression migraine aura and patent foramen ovale. Ann Neurol 2010; 67: 221–229.

41.

Bockhorst

Smith

. A quantitative analysis of cortical spreading depression events in the feline brain characterized with diffusion-weighted MRI. J Magn Reson Imaging 2000; 12: 722–733.

42.

Brennan

Beltrán-Parrazal

López-Valdés

. Distinct vascular conduction with cortical spreading depression. J Neurophysiol 2007; 97: 4143–4151.

43.

Yuzawa

Sakadžić

Srinivasan

. Cortical spreading depression impairs oxygen delivery and metabolism in mice. J Cereb Blood Flow Metab 2012; 32: 376–386.

44.

Sukhotinsky

Dileköz

Wang

. Chronic daily cortical spreading depressions suppress spreading depression susceptibility. Cephalalgia 2011; 31: 1601–1608.

45.

Eikermann-Haerter

Baum

Ferrari

. Androgenic suppression of spreading depression in familial hemiplegic migraine type 1 mutant mice. Ann Neurol 2009; 66: 564–568.

46.

Wang

Chazot

Ali

. Effects of NMDA receptor antagonists with different subtype selectivities on retinal spreading depression. Br J Pharmacol 2012; 165: 235–244.

47.

Wiedemann

Lyhs

Bartels

. The pharmacological control of neuronal excitability in the retinal spreading depression model of migraine. Curr Med Chem 2012; 19: 298–302.

48.

Eikermann-Haerter

Yuzawa

Qin

. Enhanced subcortical spreading depression in familial hemiplegic migraine type 1 mutant mice. J Neurosci 2011; 31: 5755–5763.

49.

van den Maagdenberg

Pizzorusso

Kaja

. High cortical spreading depression susceptibility and migraine-associated symptoms in Ca(v)2.1 S218L mice. Ann Neurol 2010; 67: 85–98.

50.

van den Maagdenberg

Pietrobon

Pizzorusso

. A Cacna1a knockin migraine mouse model with increased susceptibility to cortical spreading depression. Neuron 2004; 41: 701–710.

51.

Sonn

Mayevsky

. Effects of anesthesia on the responses to cortical spreading depression in the rat brain in vivo. Neurol Res 2006; 28: 206–219.

52.

Kitahara

Taga

Abe

. The effects of anesthetics on cortical spreading depression elicitation and c-fos expression in rats. J Neurosurg Anesthesiol 2001; 13: 26–32.

53.

Saito

Graf

Hubel

. Halothane, but not alpha-chloralose, blocks potassium-evoked cortical spreading depression in cats. Brain Res 1995; 699: 109–115.

54.

Guedes

Barreto

. Effect of anesthesia on the propagation of cortical spreading depression in rats. Braz J Med Biol Res 1992; 25: 393–397.

55.

Saito

Graf

Hübel

. Reduction of infarct volume by halothane: Effect on cerebral blood flow or perifocal spreading depression-like depolarizations. J Cereb Blood Flow Metab 1997; 17: 857–864.

56.

Piper

Lambert

. Inhalational anesthetics inhibit spreading depression: Relevance to migraine. Cephalalgia 1996; 16: 87–92.

57.

Verhaegen

Todd

Warner

. The influence of different concentrations of volatile anesthetics on the threshold for cortical spreading depression in rats. Brain Res 1992; 581: 153–155.

58.

Dhir

Lossin

Rogawski

. Propofol hemisuccinate suppresses cortical spreading depression. Neurosci Lett 2012; 514: 67–70.

59.

Sukhotinsky

Yaseen

Sakadžić

. Perfusion pressure-dependent recovery of cortical spreading depression is independent of tissue oxygenation over a wide physiologic range. J Cereb Blood Flow Metab 2010; 30: 1168–1177.

60.

Sukhotinsky

Dilekoz

Moskowitz

. Hypoxia and hypotension transform the blood flow response to cortical spreading depression from hyperemia into hypoperfusion in the rat. J Cereb Blood Flow Metab 2008; 28: 1369–1376.

61.

Marrannes

Wauquier

Reid

Effects of drugs on cortical spreading depression. In: Amery

Wauquier

(eds). The prelude to the migraine attack, London: Balliere Tindall, 1986, pp. 158–173.

62.

Strong

Smith

Whittington

. Factors influencing the frequency of fluorescence transients as markers of peri-infarct depolarizations in focal cerebral ischemia. Stroke 2000; 31: 214–222.

63.

Nedergaard

Astrup

. Infarct rim: Effect of hyperglycemia on direct current potential and [14C]2-deoxyglucose phosphorylation. J Cereb Blood Flow Metab 1986; 6: 607–615.

64.

Gido

Katsura

Kristian

. Influence of plasma glucose concentration on rat brain extracellular calcium transients during spreading depression. J Cereb Blood Flow Metab 1993; 13: 179–182.

65.

Hoffmann U, Sukhotinsky I, Eikermann-Haerter K and Ayata C. Glucose modulation of spreading depression susceptibility. J Cereb Blood Flow Metab. Epub ahead of print 12 September 2012. DOI: 10.1038/jcbfm.2012.132.

66.

Kilkenny

Browne

Cuthill

. Improving bioscience research reporting: The ARRIVE guidelines for reporting animal research. PLoS Biol 2010; 8: e1000412–e1000412.

67.

Eikermann-Haerter

Can

Ayata

. Pharmacological targeting of spreading depression in migraine. Expert Rev Neurother 2012; 12: 297–306.

Pearls and pitfalls in experimental models of spreading depression

Abstract

Background

Aim

Conclusion

Keywords

Introduction

In vitro vs. in vivo models

Methods to trigger SD

Methods to detect SD

Relevant SD attributes

Recommended quality measures

In vivo vs. in vitro testing

Anesthesia

Systemic physiology

Surgical preparation and maintenance

SD susceptibility

Pharmacokinetic factors

Conduct of research

Future directions and unmet needs

Footnotes

Funding

Conflict of interest

References