The urge to blink in Tourette syndrome

Abstract

Functional neuroimaging studies have attempted to explore brain activity that occurs with tic occurrence in subjects with Tourette syndrome (TS). However, they are limited by the difficulty of disambiguating brain activity required to perform a tic, or activity caused by the tic, from brain activity that generates a tic. Inhibiting ticcing following the urge to tic is important to patients’ experience of tics and we hypothesize that inhibition of a compelling motor response to a natural urge will differ in TS subjects compared to controls. This study examines the urge to blink, which shares many similarities to premonitory urges to tic. Previous neuroimaging studies with the same hypothesis have used a one-size-fits-all approach to extract brain signal putatively linked to the urge to blink. We aimed to create a subject-specific and blink-timing-specific pathophysiological model, derived from out-of-scanner blink suppression trials, to eventually better interpret blink suppression fMRI data. Eye closure and continuously selfreported discomfort were reported during five blink suppression trials in 30 adult volunteers, 15 with a chronic tic disorder. For each subject, data from four of the trials were used with an empirical mathematical model to predict discomfort from eye closure observed during the remaining trial. The blink timing model of discomfort during blink suppression predicted observed discomfort much better than previously applied models. Combining this approach with observed eye closure during fMRI blink suppression trials should therefore extract brain signal more tightly linked to the urge to blink. The simple mean of time-discomfort curves from each subject’s other trials also outperformed older models. The TS group blinked more than twice as often during the blink suppression block, and reported higher baseline discomfort, smaller excursion from baseline to peak discomfort during the blink suppression block, and slower return of discomfort to baseline during the recovery block.

The buildup of an urge in obsessive–compulsive disorder: Behavioral and neuroimaging correlates

“…In an exploratory analysis on the subset of subjects for which we had eyeblink measurements, OCD patients were less successful than controls in suppressing blinks during the blink suppression blocks but no different in overall blinking rate during the free blinking blocks. Although this eyeblink count analysis was conducted only in a subset of participants, a similar difference has been reported between patients with TD and controls (Botteron et al, ), lending credence to the findings. Overall, these data indicate that OCD patients exhibit altered brain function and behavior when experiencing and suppressing the urge to blink.…”

“…A different approach was used by Berman et al (), who employed a “sawtooth” model whereby the urge linearly increases from the beginning to the end of the suppression period. Through the analysis of continuous on‐line urge ratings obtained during 60‐s blink suppression blocks, Botteron et al () showed that an event‐related individualized model—where the urge increases up until there is a blink, after which it reduces somewhat (but not to baseline) before rising again until there is another blink—was superior to the “sawtooth” model because it accounts for temporary reductions in the urge based on accidental blinks occurring during suppression periods. Unfortunately, we could not employ an individualized blink model because we were unable to obtain a reliable measure of eyeblinks for a large portion of participants (discussed in greater detail below).…”

“…This task elicits an UFA by asking participants to suppress eye blinking alternating with free blinking. The rationale for selecting this task is based on published work using eyeblink suppression as a model for sensory-based urges in OCD and TD (Berman et al, 2012;Botteron et al, 2019;Cavanna et al, 2017;Jackson et al, 2011;Lerner et al, 2009;Mazzone et al, 2010). The design we used is similar to that employed by Berman et al (Berman et al, 2012), with blocks of normal or free blinking (30 s) alternating with longer blink suppression periods (60 s).…”

“…At the individual subject level, the primary general linear model specified regressors for blink suppression periods based on whether they were early in the period ("Hold1," the first 30 s) or late in the period ("Hold2," the last 30 s). Blocks were segregated into early and late periods in order to allow for the differentiation of brain activity based on the buildup of the urge over time, given prior work showing that the urge to blink is greater, on average, during the last half of a 60-s suppression period than the first half (Botteron et al, 2019, see below for further discussion). Blocks where subjects blinked freely ("Free") were also modeled (30 s).…”

“…To identify the overlap between group differences and a putative network associated with the buildup of the urge to blink, subject-level contrasts of Hold1 > Free, Hold2 > Free, and Hold2 > Hold1 were analyzed at the group level using one-sample t-tests for the entire sample (n = 69 subjects, results corrected for multiple comparisons at p < .05 using permutation testing as described above). A conjunction analysis probed for regions that were commonly activated for all three pairwise comparisons, reasoning that a region involved in the urge to blink would be more active during both hold blocks (early and late blink suppression) than the free blinking block and more active during late blink suppression than Through the analysis of continuous on-line urge ratings obtained during 60-s blink suppression blocks, Botteron et al (2019) showed that an event-related individualized model-where the urge increases up until there is a blink, after which it reduces somewhat (but not to baseline) before rising again until there is another blink-was superior to the "sawtooth" model because it accounts for temporary reductions in the urge based on accidental blinks occurring during suppression periods. Unfortunately, we could not employ an individualized blink model because we were unable to obtain a reliable measure of eyeblinks for a large portion of participants (discussed in greater detail below).…”