Our finding that cortical damage, exclusively in the striate cortex, results in abnormal pupil responses, is causal evidence that the pupil size is at least partially driven by a cortical process in visual areas V1-V3. This has been suggested by several perimetry studies (see (12) for a review), but also has also been hinted at by several psychophysical studies [e.g., (7, 34–36), see (9) for a review]. It is thus not unlikely that both a subcortical and a cortical pathway are responsible for the pupil light reflex. A recent investigation elegantly tried to disentangle these two pathways by stimulating either the intrinsically photosensitive retinal ganglion cells (ipRGC) or the other photoreceptors using blue or red chromatic stimuli, respectively (37). CVI patients with homonymous hemianopia only showed a weakened reflex when red stimuli were presented in a scotoma as compared to an intact visual field, suggesting that the PLR evoked through blue-light-sensitive ipRGCs are subcortically controlled while the PLR evoked through the other, red-light-sensitive photoreceptors are at least partially under control of the visual cortex. The subcortical pathway is well known, and consists of the optic nerve, LGN, pretectal nucleus (and superior colliculus), Edinger-Westphal nucleus, and ciliary ganglion (38). The cortical pathway is not yet known but it is possible that the visual cortex modulates the pupil light reflex with connections to the pretectal nucleus via the LGN (39, 40).

FIGURE 5 | The outmost left column indicates the tested models of VFDs and the other columns lists the correlation ranks with the pupil perimetry maps per patient (CVI: p1-p7; Glaucoma: p8-p15 per left (L) or right (R) eye). The model with the highest correlation with the pupil perimetry map is ranked as number 1. The rank numbers behind the VFD models as diagnosed by SAP are printed in bold, underscored font.

The presence or absence of attention for the stimuli may also play a role in enhancing or inhibiting a patient's pupil responses, respectively. More attention to a stimulus is known to enhance the pupil responses to the stimulus (7–10), also during pupil perimetry (41). When patients are aware of the presentation of a stimulus presented in an intact visual field, covert attention is automatically drawn to the stimulus (normally also saccades are drawn toward the stimulus but this was inhibited by instruction to fixate), therewith enhancing pupil responses. When a patient is unaware of a stimulus presented in a damaged visual field, covert attention is not drawn, likely remains at fixation, and pupil responses are then not enhanced. A likely neural locus that may drive these attentional effects is the superior colliculus (SC). The SC is activated during the spatial allocation of attention and gaze [e.g., (42)] and recent work suggests the SC may be part of a pathway that explains residual pupil responses to a variety of unseen stimuli in humans with blindsight (43, 44), and evoked pupil responses in monkey's (45, 46).

In addition to the theoretical impact of the current findings, we provide some practical advices for ophthalmology from the patient-related results. First, we confirm that pupil perimetry cannot dissociate patients from healthy controls by merely looking at the average sensitivity across the entire visual field (47– 52). However, large differences in pupil sensitivities across visual field locations (e.g., left vs. right visual field) can still be indicative of potential problems with vision, especially in CVI patients. We have taken a novel, quantitative approach to confirm that these differences allow diagnosis of visual impairments by comparing (i.e., statistically correlating) the overlap between objective pupil perimetry maps and subjective flicker perimetry maps.

Second, we can conclude from the results that scotomas by glaucoma are more difficult to detect with flicker pupil perimetry than scotomas caused by CVI. The improved accuracies in CVI patients could be due to decreased noise, as the pupil sensitivities of CVI patients were averaged across both eyes, filtering out noise. Pupil sensitivities of most glaucoma patients were only assessed per eye, because each individual eye shows a different pattern of VFDs. It is also possible that additional relative scotomas, were incorrectly classified as intact during the subjective perimetry tests, particularly for glaucoma patients. Future studies could try to circumvent such false positives by varying the contrast of the flicker stimulus. Low contrast stimuli presented at relative scotomas should then not be consciously detected by the patient. Another possibility that explains the differences across the two patient populations is that the visual sensitivity for flicker is less affected by glaucoma than the detection of faint targets in Humphrey perimetry. This interpretation is in line with our observation of a low overlap between the subjective flicker perimetry maps and the standard Humphrey threshold perimetry maps of glaucoma patients.

A general limitation of pupil perimetry in diagnosing glaucoma is described in a recent review on the effectiveness of pupil perimetry in studies with glaucoma patients (13). The authors explained that the diagnosis of glaucoma with pupil perimetry depends on comparisons of pupil sensitivities between locations in a damaged eye and the same locations in an intact eyes. Diagnosis becomes problematic when patterns of visual field losses are nearly or fully identical in both eyes, hampering comparisons of pupil sensitivities of intact and damaged regions between the eyes. Another limitation of pupil perimetry in general is that fine-grained patterns of visual field loss or small singular scotomas (<4 ◦ ) will be more difficult to detect with pupil perimetry because it requires the presentation of rather small stimuli at the center of the scotoma. The main problem is that small stimuli evoke weak and unreliable (variable) pupil responses. Note that the use of very large stimuli can also be problematic due to factors such as stray light (53), although a gray rather than black background may help to suppress the influence of stray light. Furthermore, the effects of stimulus size, stimulus luminance, and background luminance (i.e., light vs. dark adaptation) on pupil responses change as a function of eccentricity [e.g., (54, 55)]. These factors may also have different effects on pupil responses than on subjective visibility reports. It will be a challenge for future studies to filter out these factors in order to measure a clean form of visual sensitivity.

One limitation of the current study is that we could only detect large scotomas. Some of the glaucoma patients had relatively small scotomas and it is possible that these went undetected because the relatively large flickering disks stimulated enough intact areas around the small scotoma to evoke a strong pupil responses. Another limitation is that one glaucoma patient (P11) took pilocarpine eye drops, which has a miotic influence on the pupils and may explain the relatively weak pupil sensitivity and diagnostic accuracy in this patient. The same patient (and P14) was tested in the early afternoon, a period known to produce less reliable SAP measurements (56). A third limitation is that, in contrast to the patients, healthy controls were not extensively tested on potential problems with vision. Although the controls reported to have no problems with vision, we do not have access to information to objectify these claims.

An interesting alternative method that also circumvents this issue is a technique that presents stimuli in maximum length sequence order [e.g., (57)], which consist of the repetitive presentation of multiple black and white patches across the visual field that independently and pseudorandomly change in luminance over time. Patches that are presented inside the area of a scotoma should then explain few of the variance in pupillary dynamics. There exists another alternative, objective perimetry method termed VEP3 perimetry (58, 59) that uses electrophysiological responses as measured with EEG electrodes at the scalp near occipital regions. However, VEP perimetry may not be sensitive enough to fully dissociate patients from controls (60). One solution to this challenge would be to combine VEP perimetry and pupil perimetry to improve diagnostic accuracies (11). Lastly, pupil perimetry could be improved by combining the measurement of pupil oscillations with the measurement of the postillumination pupil response, because the latter has shown to differentiate between early glaucoma patients and healthy controls (61).

Future developments in flicker pupil perimetry may initiate a change in protocols in clinical practice. As mentioned in the introduction, pupil perimetry could perhaps diagnose visual field loss in neurologically impaired children and adults suffering from CVI, whom are unable to perform SAP. When these patients have relatively large scotomas, such as in CVI-induced hemianopia, pupil perimetry may detect the damaged locations. However, further studies on young and adult CVI patients, and healthy controls are necessary to confirm the possible application of pupil perimetry in a clinical setting as useful alternative for behavioral perimetry, such as the behavioral visual field test (BEFIE) (62), which has high specificity and sensitivity for absolute peripheral VFD (63). The objective character of pupil perimetry may also be utilized to confirm factitious VFDs when malingering is suspected. Lastly, the neural circuitry responsible for sensitivity in flicker pupil perimetry might be different from the neural mechanism that is responsible for visual awareness of faint targets in SAP. This means that pupil perimetry is an alternative, complementary test that may provide different insights in the type of scotoma than SAP.

One serious challenge for future work on pupil perimetry will be to ensure sustained attention to the task for at least 5 min. Patients with several cognitive deficits, caused by for example severe brain damage in multiple cortical regions, may not adhere to the task requirements. Although we ensured that patients paid attention to the visual stimulation by adding a letter detection task superimposed on the stimuli, forthcoming studies may invest in the development of stimuli that draw enough sustained attention, even from young children. Also the test's duration should be shortened while trying to maintain high data power and thus measurement reliability. The presentation of multiple stimuli at the same time in each eye may enable this (18, 19, 57, 64).

To conclude, the current study has demonstrated that flicker pupil perimetry is a promising diagnostic test for large VFDs, especially in patients with a CVI.

3Also known as ERP perimetry or electroperimetry.

## AUTHOR CONTRIBUTIONS

MN, CR, AF, and SD designed the experiments. MN programmed the experiments. DB, MvG, and GP recruited patients and performed standard conventional perimetry. MN, CR, and AF collected the data. MN analyzed the data. MN wrote the first drafts of the paper and all other authors helped finalizing the final paper.

## FUNDING

This research was supported by the Uitzicht grant nr. 2016-35 awarded to author AF, the grant included contributions from: Oog Fonds, FP. Fisher-Stichting, LSBS fond and Glaucoom fonds.

## REFERENCES

## ACKNOWLEDGMENTS

We thank Joris Elshout for providing us medical information about several patients and fruitful suggestions for the experimental design and analyses. We thank Tanja Nijboer and Stefan van der Stigchel for their advices. This work was supported by the Uitzicht grant nr. 2016-35 awarded to authors AF, GLP, and SOD.

## SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fneur. 2018.00558/full#supplementary-material

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2018 Naber, Roelofzen, Fracasso, Bergsma, van Genderen, Porro and Dumoulin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Pupil Cycle Time Distinguishes Migraineurs From Subjects Without Headache

#### Melissa M. Cortez 1 \*, Natalie Rae2 , Leah Millsap1 , Nick McKean1 and K. C. Brennan1 \*

*1 Department of Neurology, University of Utah, Salt Lake City, UT, United States, 2 School of Medicine, University of Utah, Salt Lake City, UT, United States*

Migraine is a neurological disorder characterized by paroxysms of head pain accompanied by trigeminovascular system activation and autonomic dysfunction. Diagnosis is currently based on clinical diagnostic criteria. Though physiological differences exist between migraineurs and non-headache controls, true physiological biomarkers have been elusive, especially for the full clinical spectrum of migraine, inclusive of chronic, episodic, and probable migraine. We used edge-light pupil cycle time (PCT) as a probe of the pupillary light circuit in migraine, paired with clinical assessment of migraine characteristics, and compared these to non-headache controls. We found significantly increased PCT in probable, episodic, and chronic migraine, compared to controls. Additionally, increased PCT correlated with the presence of craniofacial autonomic symptoms, linking pupillary circuit dysfunction to peripheral trigeminal sensitization. The sensitivity of PCT, especially for all severities of disease, distinguishes it from other physiological phenotypes, which may make it useful as a potential biomarker.

Keywords: migraine, pupil cycle time, craniofacial autonomic symptoms, central sensititization, trigeminal sensitization

## INTRODUCTION

Migraine is a common, recurrent headache disorder characterized by paroxysms of head pain accompanied by trigeminovascular system activation and autonomic dysfunction. Diagnosis is currently based on clinical diagnostic criteria and may be diagnostically categorized as probable, episodic, or chronic migraine, based on duration, number of attacks, and associated symptoms. Thus, far while clinical signs of migraine chronification (previously termed "transformation") and central sensitization are now recognized, such as cutaneous allodynia (1, 2), few human studies have shown abnormalities in physiology present across the full clinical spectrum of migraine inclusive of chronic, episodic, and especially probable migraine. In fact, to our knowledge, no physiologic test has yet been demonstrated to separate out probable migraine (PM) from non-migraineurs—a diagnostic category most practitioners consider to be clinically actionable.

Changes in pupillary function have been variably observed during the migraine headache attack (3–5), as well as inter-ictally (5, 6). Recent evidence supports the possibility of a disease gradient in the expression of pupillary responses to light, perhaps linked to the presence of photophobia (7), a well-recognized symptom of central sensitization most evident in chronic migraine (CM). Craniofacial autonomic signs and symptoms are now recognized to be relatively common in migraineurs (37–73%) and often co-occur with photophobia and allodynia (8, 9).

#### Edited by:

*Paul Gamlin, University of Alabama at Birmingham, United States*

#### Reviewed by:

*Geoffrey Karl Aguirre, University of Pennsylvania, United States Fion D. Bremner, University College London, United Kingdom*

#### \*Correspondence:

*K. C. Brennan<EMAIL_ADDRESS>Melissa M. Cortez<EMAIL_ADDRESS>
#### Specialty section:

*This article was submitted to Neuro-Ophthalmology, a section of the journal Frontiers in Neurology*

Received: *20 November 2018* Accepted: *23 April 2019* Published: *08 May 2019*

#### Citation:

*Cortez MM, Rae N, Millsap L, McKean N and Brennan KC (2019) Pupil Cycle Time Distinguishes Migraineurs From Subjects Without Headache. Front. Neurol. 10:478. doi: 10.3389/fneur.2019.00478*

**297**

These facial signs and symptoms are thought to arise from peripheral nociceptive activation of the trigeminal-autonomic reflex, leading to efferent activation of cranial nerves targeting the nasal mucosa, lacrimal glands, other facial structures (10). Alterations in the pupillary light reflex (PLR), in the setting of central sensitization, may occur by similar mechanisms (11), though the relationship between pupillary function and craniofacial autonomic symptoms (CAS) has not been directly explored.

Edge-light pupil cycle time (PCT) was initially developed by Miller and Thompson in 1978 as a test of optic nerve afferent pathway disease (12). Soon after, the technique was extended for use as a screen of the pupil's entire light reflex arc, inclusive of efferent pupillary pathways (13). Pupil cycle time has shown sensitivity for both parasympathetic (14) and sympathetic (15) disorders of the PLR. Thus, we deployed PCT for the assessment of the pupillary light circuit in migraine, paired with clinical assessment of migraine characteristics.

## MATERIALS AND METHODS

## Participants

In total, 98 subjects (31 male/67 female) aged 15–75 years were recruited into two groups: (1) migraine headache, and (2) age and sex-matched non-headache (NH) controls. Subjects were recruited between June 2015 and September 2018, from local community and the University Neurology Headache and General Neurology clinics, as well as community volunteers via word of mouth, internet, and flier advertisements. Institutional Review Board approval was obtained from the University of Utah Human Studies Committee (IRB\_00085309 and IRB\_00064447). All participants completed written informed consent; for those under the age of 18, participant assent, paired with parental (or legal guardian) informed consent and permission, were obtained. Headache diagnosis was based on 2013 International Classification of Headache Disorders III-beta criteria (16). Upon completion of a structured clinical questionnaire (described further below), the migraine group was further divided into episodic migraine (EM), chronic migraine (CM), and probable migraine (PM) for a total of 73 headache subjects (28 migraine with aura, 45 migraine without aura).

Episodic and probable migraine participants were studied after being headache-free for at least 48 h, and subjects were excluded if a migraine occurred within 24 h of testing. Chronic migraine subjects were studied when migraine attackfree for at least 48 h, though testing during daily or nonmigrainous headaches was permitted. Subjects had not used opiate medication or migraine-specific abortive medications during the 48 h prior to testing. Headache diaries were used to assess attack frequency for 1 week prior to testing and for subsequent attacks occurring within the 2 weeks of testing, as well as medication use. Subjects did not take medications (including eye drops other than artificial tears, or prophylactic treatment for migraine, including psychotropics, antihistamines, benzodiazepines, barbiturates, and derivatives), and denied a history of comorbid medical, ocular, or neurological disorder (e.g., prior eye injury, idiopathic blepharospasm, optic nerve disorder), that is known to directly affect autonomic function or pupillary control (including diabetes). Subjects were instructed not to consume alcohol, caffeine or nicotine for at least 4 h prior to testing. The group of age and sex matched control subjects reported no history of headache and were studied in their usual state of health.

## Measurements

### Questionnaire

Subjects completed a modified written Structured Migraine Interview (17) along with a headache diary to characterize migraine diagnosis and headache frequency. The Migraine Disability Assessment (MIDAS) (18), Headache Impact Test (HIT-6) (19), Fatigue Severity Scale (FSS) (20), Patient Health Questionnaire (PHQ-9) (21, 22) and Generalized Anxiety Disorder (GAD-7) (23, 24) were also collected to assess headache impact and related disability, as well as fatigue and affective symptoms. As there are no currently available, validated tools for headache-associated cranial autonomic symptoms (CAS), we based our assessment on those used by Gelfand et al. (25) and the ICHD-III proposed definition of CAS (26). Subjects replied "yes" or "no" to the following eight symptoms associated with their usual headache: conjunctival injection or lacrimation, nasal congestion or rhinorrhea, eyelid swelling, forehead/facial sweating, forehead/facial flushing, changes in pupil size, droopy eyelid, sense of fullness in the ear.

## Edge-Light Pupil Cycle Time (PCT)

Edge-light PCT was assessed using methods adapted from Miller and Thompson (12) as a measure of the relative integrity of both afferent and efferent pupillary pathways. This technique differs from other types of pupillary oscillations (27), which tend to be of irregular cycling duration, including that of pupillary unrest (e.g., hippus) (28), which occurs under diffuse illumination, and from the significantly slower, rather episodic, pupillary oscillations that occur under dark conditions in the fatigued or drowsy subject (29–32). In contrast, edge-light PCT uses a directed, narrow beam of light at the pupil edge, which exploits the normal pupil's light reflex arc and produces a fairly brisk, and regular oscillation. Pupil cycle time has been shown to be stable across repeated testing and is not significantly affected by refractive error, sex, or iris color (12, 13). Thus, we selected this assessment as a simple method for assessing overall pupil responsiveness to light across groups.

The examination set-up, and a representative example of pupil diameter change over time with this technique is shown in **Figure 1**. In this test, the subject is seated at a slit-lamp in a dimly lit room (<1 lux) and asked to gaze toward a designated object consistent with the subject's far point. After a 3-min dark adaptation period, a horizontally oriented beam of light (5 mm wide, 0.5 mm thick) is positioned just below the inferior aspect of the pupillary margin, and slowly elevated until it contacts the inferior edge of the pupil. The intensity of the light beam, range 10–100 lux, was kept at the lowest intensity necessary to produce pupil constriction, in order to maximize subject comfort for the duration of the test. In normal subjects, the light beam induces brisk pupillary constriction, moving the pupillary margin

outside of the light stimulus; the pupil then spontaneously redilates until encountering the beam once again, creating a cycle. Here, the examiner maintains the location of the light beam in order that the iris remains outside the light while constricted, but re-contacts the light upon re-dilation. One cycle is counted as one pupillary constriction, followed by re-dilation; each cycle is observed and counted through the binocular scope of the slit lamp. According to previously published methods, after regular cycling is established (typically 2–3 oscillations), a total of 100 cycles, divided into 3 trials of 30, 30, and 40 cycles each, are directly visualized and counted by the examiner; cycle time is then reported in milliseconds/cycle (msec/cycle) (12, 14). In order to minimize learning curve and the risk of systematic biases, all examiners were trained by the same experienced examiner, blinded to study group, and used a standardized script for instructions to the study subject.

For analysis purposes, the overall pupil cycle time for each eye was determined by averaging the three trials for each eye. Prior authors have noted occasional irregular beats of constriction, superimposed on the regular oscillations of the edge-light based cycling; these "mini-fluctuations" are thought to represent superimposed "pupillary unrest," and thus examiners were trained not to count these (12). Cycle time was not identical between sides, though there were no significant differences in PCT between right vs. left eyes in either the NH nor the Migraine-All group (Wilcoxon signed-Rank test, p = 0.68 and 0.80, respectively). For the purposes of analysis, we used the longest of the two sides, according to previously published methods (14). All experiments were performed in a quiet, controlled environment, to limited external sources of excitation.

### Baseline Pupil Size

Baseline pupil size data was obtained in a separate protocol, performed during the same testing session, prior to PCT data collection. Here, dark-adapted pupil size was obtained after a 10 min acclimation period to the testing environment, and an additional 1 min of dark adaptation using a binocular pupillometer (DP-2000, Neuroptics Inc, Irvine, CA; image acquisition 30 Hz, pixel resolution 0.05 mm).

#### Statistical Methods

Visual inspection of the data, followed by Shapiro-Wilk normality test, was applied to each parameter to assess for distribution of data. Overall, our test parameters were not normally distributed, thus Kruskal-Wallis was utilized for across group comparisons, and Wilcoxon rank sum test was used for post-hoc pair-wise comparisons. In these instances, p-values were considered significant only following Bonferroni correction for multiple comparisons. Correlations were made initially using two-tailed Spearman's correlation as a conservative method, and confirmed with age-adjusted partial correlations with Holm's correction for multiple comparisons. Multiple regression analysis, using standard least squares method with Box-Cox transformation as indicated, was performed to evaluate effect of the following covariates: PCT with anxiety (GAD) + depression (PHQ) + fatigue severity (FSS), and PCT with baseline pupil + age. A Bland-Altman assessment for inter-rater agreement was used to compare PCT calculations between two raters for a selected subset of data (n=17). Finally, measurement dispersion between trials 1 and 3 of PCT within the control and migraine groups was assessed using quartile coefficient of variation. Results were considered significant for p–values ≤ 0.05, except where Bonferroni was applied. Statistical analyses were performed with R for Windows (Version 3.5.1; R Core Team, Vienna, Austria) and JMP version 14.2.0 (2019, Windows).

## RESULTS

Baseline characteristics and headache-specific clinical characteristics are summarized in **Tables 1**, **2**, respectively. There were no significant differences in age or sex-distribution between the NH and migraine groups. Migraine subjects reported significantly more depression (PHQ-9), anxiety (GAD-7), and fatigue (FSS) related symptoms than NH controls. Age of headache onset did not significantly differ between migraine subgroups. As expected, based on diagnostic criteria, headache days per month was significantly higher in CM subjects; similarly, MIDAS and HIT-6 scores were significantly higher in CM than EM and PM.

## Pupil Cycle Time (PCT)

Longest pupil cycle time was significantly different across all groups (Kruskal-Wallis rank sum test, p = 0.00001) (**Figure 2**). Pair-wise comparisons (2-sample Wilcoxon test) confirmed a significantly longer PCT in PM vs. NH (p = 0.0005), EM vs. NH (p = 0.001), and CM vs. NH (p < 0.0001). While there were no significant differences across migraine sub-groups (Kruskal-Wallis rank sum test, p = 0.38), median values appear to show a gradient between NH<PM<EM<CM. See **Table 3** for data summary.

The significant difference seen between the NH vs. Migraineall groups remained significant after Box-Cox transformation and least squares multiple regression analysis controlling for GAD + PHQ + FSS (p = 0.03); subgroup comparisons maintained significance or trended toward significance (NH vs. PM, p = 0.1; NH vs. EM, p = 0.1; NH vs. CM, p = 0.0009). There were no significant differences in baseline pupil sizes across NH and migraine groups (p = 0.99). PCT remained significantly longer in the migraine groups after controlling for dark-adapted baseline pupil diameter and age (NH vs. Migraine-All, p = 0.02; NH vs. PM, p = 0.01; NH vs. EM, p = 0.1; NH vs. CM, p = 0002). TABLE 1 | Clinical characteristics.

*F, female; FSS, Fatigue Severity Score; GAD, Generalized Anxiety Disorder; max, maximum; min, minimum; PHQ, Patient Health Questionnaire.*

*Sex: chi-square test.*

*Age, Fatigue Severity, PHQ, GAD: Wilcoxon rank sum test.*

#### TABLE 2 | Migraine group clinical characteristics.

*CAS, craniofacial autonomic symptoms; CM, chronic migraine; EM, episodic migraine; HA, headache; HIT, Headache Impact Test; max, maximum; MIDAS, Migraine Disability Assessment; min, minimum; PM, probable migraine.*

*Age, HA days, MIDAS, HIT, CAS: Wilcoxon rank sum test.*

One or more headache-associated CAS were reported in 29 of 73 (40%) of headache subjects overall; of these, CAS were most commonly reported in CM (48%), followed by EM (40%) and PM (36%). Pupil cycle time significantly correlated with number of CAS in the Migraine-All group (Spearman rho 0.40, p=0.04). Within the migraine group (n=73), 19% reported at least one unilateral CAS, which corresponded with their typical headache side; 39% reported alternating CAS; and 42% reported bilateral CAS. Forty-four of the 73 headache subjects (60%) reported habitual lateralization of headache location; within this group, there was no significant difference between right and left PCT (paired-sample Wilcoxon test, p = 0.24), nor were there significant differences between PCT in headache subjects who reported alternating, lateralizing or non-lateralizing headaches (Kruskal-Wallis rank sum test, p = 0.34). Finally, PCT did not differ significantly in those who reported unilateral CAS, compared to their non-symptomatic side.

## Inter-rater Agreement and Measurement Dispersion of Pupil Cycle Time

In our study, there were no significant differences in PCT between examiner groups of NH (p = 0.23) and migraine (p = 0.25). Additionally, Bland-Altman assessment for agreement between two raters on a subset of data (n = 17) indicated that the 95% limits of agreement between the two methods ranged from of −36.83–796.09, with a correlation coefficient of r = 0.79.

Measurement dispersion was similar between trials 1 and 3 of PCT in both NH and Migraine-All, though more variability was noted in the Migraine group overall: quartile coefficients of variation of 0.11 and 0.10 (NH), and 0.23 and 0.28 (Migraine-All), respectively.

## DISCUSSION

Our study provides insight into the integrated pupillary response to light in migraine headache, and links this network output to craniofacial autonomic signs and symptoms. We show that PCT is significantly prolonged across all migraine subjects, with an apparent disease gradient of PCT prolongation across clinical subgroups (CM>EM>PM>NH; **Figure 2**). Our data show that migraine subjects, including those with PM under ICHD-III-beta definitions, can be distinguished from healthy NH controls, not only on the grounds of symptomatic profile, but also physiological measures.

#### TABLE 3 | Pupil testing.

Furthermore, we found a significant correlation between PCT and CAS, with increasing PCT in those with the greatest number of craniofacial autonomic symptoms, which also exhibit the same disease gradient (**Table 2**). While, peripheral trigeminal sensitization in migraine is thought to be a prerequisite for the head pain itself (10, 33), headache attack-associated CAS may reflect a more marked or prolonged underlying peripheral trigeminovascular sensitization, and are associated with a higher disease burden (9). Interestingly, those with unilateral CAS have been noted to benefit more from 5-HT-1B/1D agonist-based treatments than those without CAS (34). Further study is needed to understand whether PCT might be a useful objective tool to study treatment responsiveness.

## Relationship of Pupillary and Cranial Autonomic Symptoms to Peripheral and Central Sensitization in Migraine

Patients with co-existing allodynia and photophobia—both well-recognized signs of central sensitization—are also more likely to report headache-associated CAS (9), implicating CAS in the process of central sensitization as well as peripheral trigeminal sensitization (10). Thus, far while multiple clinical signs of migraine chronification and central sensitization are now measurable through quantitative sensory testing and questionnaires, few studies have shown abnormalities in objective physiology present across the full clinical spectrum of migraine inclusive of chronic, episodic, and in particular, probable migraine. We show data linking pupillary responses to light in migraine, to signs of peripheral trigeminal and central sensitization, with longer PCT correlating with increased frequency of headache-associated craniofacial autonomic signs and symptoms. This finding builds on recent findings showing altered pupillary light responses in migraineurs with the lowest light sensitivity thresholds (7). Future investigation into the relationship of light sensitivity, allodynia, and quantitative pupillary responses to light will aid in parsing these relationships.

While CAS can correspond with habitual headache side (19% in our study), a majority of adult migraineurs report bilateral or alternating CAS (81% in our study; 67–95% in Lai et al.) (35). Based on this, it is not surprising that we did not see significant relationships between CAS laterality and PCT asymmetry. Further, this may provide preliminary data to support the possibility that PCT reflects underlying circuit dysfunction, which is not necessarily lateralizing. Though, given the relatively small proportion of our sample with unilateral CAS,

*CM, chronic migraine; EM, episodic migraine; max, maximum; mm, millimeter; min, minimum; msec, millisecond; PM, probable migraine; PCT, pupil cycle time.* \**Significant difference from control.*

we were likely underpowered to detect significant relationships between strictly lateralizing CAS and PCT.

## Implications to Our Understanding of Migraine Headache

In this study, we utilized edge-light PCT, which was originally developed as a measure of the relative integrity of both afferent and efferent pupillary pathways, and thus a measure of the integrated pupillary circuit response. The first applications of this method were in afferent disorders (retinal and optic nerve dysfunction) (36–38), though it fell out of favor for this use with the development of more specific methods for optic nerve assessment (39). Subsequent studies have supported use of PCT for evaluation of both parasympathetic and sympathetic lesions of the PLR reflex arc. Martyn and Ewing (14) applied the technique in subjects with diabetic autonomic neuropathy, where PLR correlated with abnormal cardiovascular autonomic function, and was pharmacologically localized to the efferent (parasympathetic) limb of the PLR arc (14). Blumen et al. applied PCT in subjects with unilateral Horner's syndrome, and showed prolongation in central, preganglionic, and postganglionic sympathetic lesions (15). In our study, in the absence of adjunct pharmacological or quantitative PLR testing, we are not able to make conclusions regarding localization of underlying parasympathetic vs. sympathetic dysfunction, though our data could be seen as consistent with prior observations of mixed sympathetic and parasympathetic hypofunction in migraineurs in the inter-ictal phase (6, 7, 40, 41). Though the literature is mixed, and the majority show relatively subtle differences and/or variable patterns between groups (5, 42).

Beyond sympathetic and parasympathetic localization, we favor the interpretation of PCT as a sensitive (but not completely specific) indicator of whole pupillary circuit (dys)function, with the potential to detect, or even amplify, subtle changes in pupillary light responses, including those of central origin (43), which are of particular interest in migraine where cortical processing and central sensitization are implicated (10). Foundational studies, featured in a historical review by Lowenstein and Loewenfeld (29), highlighted the role of not only brainstem mediated sympathetic and parasympathetic influences on maintenance of the PLR arc, but also importantly, cortical influences. More contemporary methods have explored the role of central control of autonomic outflow to the iris with particular attention to spontaneous oscillations of pupil size under both light and dark conditions (27, 43, 44); premotor autonomic nuclei, including the paraventricular nucleus of the hypothalamus, and the dorsal raphe nucleus and locus coeruleus of the midbrain, are light sensitive and are of particular interest when considering centrally mediated responses to light.

Current understanding of migraine pathophysiology implicates multiple common neuroanatomical sites within the PLR arc (10, 44): cortical and hypothalamic projections provide descending modulation via the periaqueductal gray (PAG), nucleus cuneiformis (NCF), and rostroventromedial medulla (RVM), which have also been implicated in models of pain sensitization; direct projections from the paraventricular nucleus (PVN) of the hypothalamus to the trigeminal nucleus caudalis (TNC) are implicated sites in migraine models. The PAG and PVN are both involved in the classically recognized "light-inhibited" sympathetic pupillary pathways, where light causes a sympatho-inhibitory effect. As the circuit mechanisms of migraine remain poorly understood, we can only speculate at this point on the ultimate source of migraine-associated dysfunction; however it is likely that, as with other disorders of circuit function (rather than, for example, "lesion"-based disorders like stroke or multiple sclerosis) the phenotype arises from altered synaptic weighting within the circuit, rather than the destruction or explicit dysfunction of any one circuit element (10, 44).

## LIMITATIONS

In our study, the range of PCT observed in normal individuals was broader than previously reported normal control groups, where the reported normal upper limit was 935–946 (36). This highlights one of the pitfalls of PCT, in that it is observer dependent, and may be artificially prolonged by undetected cycles, interruption by frequent blinking, or need to follow a moving pupil in cases of eye movement (45, 46). To address this, the first 50 subjects were collected by a single investigator (9 NH and 41 migraineurs), with the second half (48 total; 16 NH and 32 migraineurs) of our sample performed by two other individuals trained by the original investigator. In our study, inter-rater variability appeared minimal (as above in Results, Inter-rater agreement and measurement dispersion of pupil cycle time section), though in working with this technique, it is evident that the method would benefit from updating, including use of currently available dynamic pupillometry and objectively defined cycle counting parameters.

As with most complex physiological mechanisms, the broad array of involved structures complicates interpretation. We have attempted to address this through careful screening of medical history for confounding ocular or central nervous system disorders. It is also well-recognized that differences in fixation and stimulus luminance can result in variable changes in amplitude and latency of pupil contraction (47), which could alter PCT. Thus, our protocol included a strict point of visual fixation to decrease eye movement and fixation-based pupillary changes, a standardized light stimulus, and trials where blinking or eye movement disrupted reliable recording of PCT were discarded (4 trials total across all subjects). Additionally, some might mistake PCT for measurement of pupillary "unrest" (aka hippus), for which the underlying mechanisms are unknown. However, as discussed above, hippus is inherently irregular with variable amplitude, and is present in diffuse (rather than a focused beam) illumination (12), which were importantly not the characteristics of the edge-light PCT elicited by our protocol.

## CONCLUSIONS

Our data shows that migraine subjects, including for the first time those with probable migraine, can be distinguished from NH controls not only on the grounds of symptomatic profile, but also on physiological measures. Furthermore, we show data linking pupillary responses to light to signs of peripheral trigeminal and central sensitization, with increases in PCT correlating with increased craniofacial autonomic signs and symptoms. Finally, while PCT does not have circuit localizing function without pharmacological manipulation, we have shown data revealing significant differences in pupillary physiology between non-headache controls, and migraineurs—inclusive of probable migraine. Given that PCT is relatively simple, and could be amenable to automation and standardization of methodology, such a tool could be used to detect the earliest phases of peripheral trigeminal sensitization, potentially identifying opportunities for early intervention, as emerging "disease modifying" therapies in migraine are deployed.

## ETHICS STATEMENT

This study was carried out in accordance with the recommendations of The University of Utah Institutional Review Board (IRB) with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the University of Utah IRB. This study did not involve vulnerable populations.

## REFERENCES

## AUTHOR CONTRIBUTIONS

MC, NR, and KB conceived of and planned the experiments, as well as conducted recruitment. NR performed the measurements and data collection, MC supervised the data collection. MC, LM, and NM processed the experimental data and performed analysis. KB aided in interpreting the results. MC drafted the first draft of the manuscript and drafted the figures. NR wrote sections of the manuscript. KB wrote sections and edited the manuscript. LM and NM reviewed and edited the manuscript. All authors take responsibility for the contents of the manuscript.

## FUNDING

NIH NIMHD LRP (MC); American Academy of Neurology Medical Student Summer Research Program (NR); Fairclough Endowment for Headache Research (LM); NIH NINDS R01 NS 085413, NS 102978 (KB, NM).

## ACKNOWLEDGMENTS

Jeremy Theriot for concept design and production of illustrations.

3rd edition. Cephalalgia. (2018) 38:1–211. doi: 10.1177/03331024177 38202

Kerrison JB, editors. Walsh and Hoyt's Clinical Neuro-Ophthalmology. Philadelphia, PA: Lippincott Williams & Wilkins (2005). p. 724–6.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Cortez, Rae, Millsap, McKean and Brennan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.


**Author details**

Gabriela Lopes dos Santos1 , Kaique Preto Alberto1 , Silas Antonio Juvêncio de Freitas Filho1 , Kellen Cristine Tjioe2 and Denise Tostes Oliveira1 \*

1 Department of Surgery, Stomatology, Pathology and Radiology, Area of Pathology, Bauru School of Dentistry, University of São Paulo, Bauru, Brazil

2 Department of Surgery, Stomatology, Pathology and Radiology, Area of Stomatology, Bauru School of Dentistry, University of São Paulo, Bauru, Brazil

\*Address all correspondence to<EMAIL_ADDRESS>
© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

*Oral Cancer around Dental Implants: Are the Clinical Manifestations and the Oncogenic… DOI: http://dx.doi.org/10.5772/intechopen.101156*


**3. Advanced nonthermal technologies**

Conventional thermal processing such as blanching and pasteurization can result in oxidation and other deleterious reactions that lower the levels of phytonutrients in processed foods [28–30]. For example, canned fruits and vegetables undergo retort processing temperatures in excess of 100°C to obtain commercial sterility. This can lead to significant losses in anthocyanin content, up to 70%, observed in the processing of strawberries into jam. Advanced nonthermal technologies are able to achieve preserving effects at sub-lethal temperatures (up to 40°C). These methods retain higher phytochemical content whilst minimally changing the sensorial properties of the food [29]. The stability of phytochemicals in thermally processed fruits and vegetables decreases exponentially with a linear increase in both the magnitude and duration of the heating process [30]. The use of nonthermal treatments at successfully lower temperatures and times provide real alternatives from traditional thermal processing through the production of additional health promoting-benefits and maintaining the desired *"fresh-like"* quality of foods for consumers [28, 29]. The present review will focus on the effects of the following novel technologies: pulsed electric field (PEF), high pressure processing (HPP), pulsed light (PL), cold plasma (CP) and ultrasound (US) on food quality and stability of phytochemicals particularly in fruit and vegetable products. These findings are reported below and summarized in **Table 1**.

(HBAs) and hydroxycinnamic acids (HCAs). Phenolic acids are seldom found in mangoes, berries, citrus fruits, red wine and plums. Their main benefits to human health are the preven-

Anthocyanins belong to the widespread group of plant constituents called flavonoids. In fruits and vegetables, they are responsible for the orange, red, purple and blue colors. Such dietary antioxidants aid in preventing neuronal diseases, heart diseases, cancer, diabetes and inflammation [23]. According to a study by Zhao et al. various commercial extracts of anthocyanin rich grapes, bilberry and chokeberry were prepared. When investigated for their chemopreventitive effects against colon cancer, it was found that all of the extracts inhibited the growth of HT-29 colon cancer cells [24]. In another study conducted by Wang and Mazza [25], the inhibitory effects of anthocyanins found in selected berries against nitric oxide (NO) were investigated. Since NO is associated with many chronic inflammatory diseases, the strong inhibition of anthocyanins on NO production indicated that anthocyanins can aid in

Phenolic acids are a major source of dietary phenolics belonging to the non-flavonoid group of phytochemicals. Two major groups are HBAs and HCAs as noted above [25]. HCAs are found in many conjugated forms, with p-coumaric, caffeic, ferulic and sinapic acids being the most common and in HBAs; p-hydroxybenzoic, vanillic, syringic and protocatechuic are the most common. Phenolic acids are often found in berries such as strawberries, raspberries and blackberries [26]. Studies conducted on caffeic acid have shown that phenolic acids possess

Conventional thermal processing such as blanching and pasteurization can result in oxidation and other deleterious reactions that lower the levels of phytonutrients in processed foods [28–30]. For example, canned fruits and vegetables undergo retort processing temperatures in excess of 100°C to obtain commercial sterility. This can lead to significant losses in anthocyanin content, up to 70%, observed in the processing of strawberries into jam. Advanced nonthermal technologies are able to achieve preserving effects at sub-lethal temperatures (up to 40°C). These methods retain higher phytochemical content whilst minimally changing the sensorial properties of the food [29]. The stability of phytochemicals in thermally processed fruits and vegetables decreases exponentially with a linear increase in both the magnitude and duration of the heating process [30]. The use of nonthermal treatments at successfully lower temperatures and times provide real alternatives from traditional thermal processing through the production of additional health promoting-benefits and maintaining the desired *"fresh-like"* quality of foods for consumers [28, 29]. The present review will focus on the effects

the ability to inhibit antitumor activity against colon carcinogenesis [27].

tion of stroke, cancer and coronary heart diseases [22].

192 Phytochemicals - Source of Antioxidants and Role in Disease Prevention

the prevention of chronic inflammatory diseases [25].

**3. Advanced nonthermal technologies**

*2.2.1. Anthocyanins*

*2.2.2. Phenolic acids*

**3.1. Pulsed electric field (PEF)**

Adapted from Toepfl et al. [32].

Pulsed electric field (PEF) involves the direct application of short, high current voltage pulses that create an intense electric field, applied to a food matrix placed between two electrodes [31]. PEF has been used as an alternative nonthermal treatment in the pasteurization of liquid or pumpable foods. Fruit juices, milk, smoothies, yogurt, sauces, wine, and soup-based products contain large amounts of water and dipolar molecules making them more conductive for passage of electrical currents compared to solid type foods. The PEF system discharges a high voltage pulse uniformly throughout the food in a treatment chamber (see **Figure 1a**) [29, 32]. Typical field strengths varies from 0.1 to 80 kV/cm with the time duration of the pulse cycles ranging from *μs* to *ms* depending on the application of PEF. The mechanism of PEF is best explained using the *"electroporation"* model in which the strong electric fields generated induce either reversible or irreversible (depending on electric field intensity) perforation of the cytoplasmic membrane promoting cell leakage (see **Figure 1b**) [31]. This effect has shown inactivation of microorganisms and food spoilage enzymes, thereby enhancing food safety, quality and phytochemical yield and extraction.

An Evaluation of the Impact of Novel Processing Technologies on the Phytochemical…

http://dx.doi.org/10.5772/intechopen.77730

195

Kumar et al. on investigating the effect of PEF on carotenoids, microbial stability and different physicochemical changes on ready-to-drink (RTD) mango nectar, noted a high retention of carotene content (94.2%) and minimal changes in total soluble solids (TSS), pH acidity and color [33]. In a separate study [34], a higher retention of volatile monoterpene compounds, in particular (Z)-Ocimene, in mango nectar pasteurized at 96°C for 300 and 600 s was observed. Sensory scores conducted also found PEF samples to be insignificantly different from control samples owing to retention in volatile components and reduction in nonenzymatic 5-hydroxy methyl furfural (HMF) brown compounds. As cited in Buckow et al. several studies surveyed the effects of PEF on orange juice treated at ≤68°C, resulted in maintenance of vitamin C, carotenoid, polyphenol, and volatile aroma compounds compared to thermal pasteurization

**Figure 1.** (a) Configuration of treatment chambers for continuous PEF processing: (i) parallel plate, (ii) coaxial, and (iii) co-linear; and (b) effects of exposure of biological cells at different electric field strengths and applications in food.

PEF is capable of extracting compounds such as pigments, antioxidants and flavors through the ability of the electric fields to induce cell membrane breakdown in plant tissue, increasing the

(95°C for 30 s) both after processing and refrigerated storage [35].

**Table 1.** Impact of nonthermal processes on food quality and phytochemical compounds.


4.3.4. Impulse Response

Since the VAR model contains many parameters, it cannot directly explain the economic meaning of parameters, so it is mainly analysed through the impulse response. Figure 7 shows the impulse response of the Taiyuan atmospheric environment system comprehensive index U1 and the industrial system comprehensive index U2. The horizontal axis represents the lag order of impact (unit: year), and the vertical axis represents the response value of relevant variables. It can be seen from the figure that when the comprehensive index U1 of the atmospheric environment system was used as the pulse variable, the comprehensive index U2 of the industrial system fluctuated significantly during phases 3–5, which shows that the optimisation of the atmospheric environment system will have a positive impact on the industrial system in the medium and long term. When the industrial system comprehensive index U2 was used as the impulse response variable, the atmospheric environment system comprehensive index U1 had positive benefits in phases 3–5, but the benefits were small.

#### **Figure 7.** Impulse response.


**3. Research Methodology**

In this section, we will introduce a neutrosophic forecasting model for time series based on first-order state and information entropy of high-order fluctuation. The detailed steps are shown as follow steps and in Figure 1.

**Figure 1.** The flowchart of the neutrosophic forecasting model.

#### *3.1. Step 1: Using Neutrosophic Fluctuation Sets to Describe a Time Series*

Let {*Vt*|*t* = 1, 2, 3, ... , *T*} be a stock index time series and {*Ut*|*t* = 2, 3, ... , *T*} be its fluctuation time series, where *Ut* = *Vt* − *Vt*−1 *(t* = 2, 3, ... , *T)*. Then, we can calculate *len* = *T t*=2 |*Ut*| *T*−1 , which is the benchmark for interval division when calculating membership. Let {*Xt*|*t* = *m*, *m* + 1, *m* + 2, ... , *T*} be the *m*th-order neutrosophic expression of fluctuation time series {*U*t|*t* = 2, 3, ... , *T*}. The conversion rules for the truth-membership *TXt*and falsity-membership *FXt*of *Xt* are defined as follows:

$$T\_{X\_{\ell}} = \begin{cases} 0, & \text{l} \text{l}\_{\ell} \le -0.5 \text{l} \text{en} \\ \frac{\text{l}\_{\ell}}{3/2 \times \text{len}} + \frac{1}{3}, & -0.5 \times \text{len} \le \text{l} \text{l}\_{\ell} \le \text{len} \\ 1, & \text{l} \text{l}\_{\ell} \ge \text{len} \end{cases} \qquad F\_{X\_{\ell}} = \begin{cases} 1, & \text{l} \text{l}\_{\ell} \le -\text{len} \\ \frac{-\text{l} \text{l}\_{\ell}}{3/2 \times \text{len}} + \frac{1}{3}, & -\text{len} \le \text{l}\_{\ell} \le 0.5 \times \text{len} \\ 0, & \text{l} \text{l}\_{\ell} \ge 0.5 \text{len} \end{cases} \tag{7}$$

#### *3.2. Step 2: Using Information Entropy to Represent the Complexity of Historical Fluctuations*

*{Ut*|*t* = 1, 2, 3, ... , *T*} can be fuzzified according to a linguistic set *L* = {*l*1, *l*2, *l*3, *l*4, *l*5}. Specifically, *l*1 = [ *U*min , −1.5×*len*), *l*2 = [−1.5×*len* , −0.5×*len*), *l*3 = [−0.5×*len* , 0.5×*len*), *l*4 = [0.5×*len* , 1.5×*len*), and *l*5 = [1.5 × *len* , *U*max). The conversion rule for the indeterminacy-membership *IXt* is defined as follows:

$$I\_{\mathcal{X}\_l} = -\sum\_{n=1}^{\mathcal{S}} p\_{\mathcal{X}\_l}(L\_n) \log\_2(p\_{\mathcal{X}\_l}(L\_n)) \tag{8}$$

where *g* = *5*, *pXt*(*Ln*) indicates the probability of occurrence of the label *ln* in the past *m* days.

## *3.3. Step 3: Establishing Logical Relationships for Training Data*

According to Definition 5, NLRs were established as a training dataset.

#### *3.4. Step 4: Calculating the Similarities between Current Data and Training Data*

According to Definition 6, similarities between current data and training data were calculated. Let *t* be the current data of the point. *SXt*,*j* is the similarity of NFTS between the current point *t* and training data *j*.

#### *3.5. Step 5: Forecasting Neutrosophic Value Using the Aggregation Operator*

According to Definition 7, the future neutrosophic fluctuation number *Xt*+1 can be generated based on the training dataset and the similarities with *Xt*. In order to eliminate very low similarity data, valid NLRs satisfy *SXt*,*j*≥ *w*- .

#### *3.6. Step 6: Deneutrosophication for the Neutrosophic Fluctuation Set and Calculating the Forecasted Value*

Calculating the expected value of the forecasted neutrosophic set *Xt*+1, the forecasted fluctuation value can be calculated by:

$$V\_{t+1}' = (T\_{X\_{t+1}} - F\_{X\_{t+1}}) \times len + \mathbf{V}\_t \tag{9}$$