Motor impairment was quantified in patients using a modified version of the cerebellar motor deficit scale (Motor score) proposed by Apollonio and colleagues [42] , which ranges from 0 (absence of any deficit) to 42 (presence of all deficits to the highest degree) and evaluates eight clinical signs (dysarthria, limb tone, postural tremor, upper and lower limb ataxia, standing balance, gait ataxia and ocular movements).

Patients' cognitive profiles were evaluated extensively using a battery of tests ( Table 3 ), including WAISr total intelligence quotient values (TIQ), immediate (IR) and delayed (DR) recall of Rey's 15 words [29] , immediate visual memory (IVM) [30] , forward (FDS) and backward digit span (BDS), forward (FC) and backward (BC) Corsi Test [31] , Raven's 47 progressive matrices (PM) [32] , freehand copying of drawings (CD) [33] , temporal rules induction [34] , and word fluency (WF) [35] . FCb patients had generally preserved cognitive patterns. The lack of clinical deficits is consistent with studies that have reported cognitive impairments only under ad hoc test conditions [36–41] .

Thirteen FCb subjects were enrolled; their aetiologies and lesion characteristics are listed in Table 1 . The inclusion criteria were no clinical or neuroradiological evidence of extracerebellar pathologies, forming subgroups of similar numerosity with regard to involvement (FCb+; n.7) or noninvolvement (FCb−; n.6) of deep cerebellar nuclei (DCN) in the lesions (as determined by magnetic resonance imaging [MRI]; see below)–the significance of DCN in cognition has recently been highlighted, because they facilitate cerebellar-thalamo-cortical connections [27,28] . The control group comprised 22 subjects, matched for sex, age, and education, with no history of neurological or psychiatric illness. The demographics and education of the groups are shown in Table 2 .

Each individual lesion is presented as an overlay of 2 representative coronal MRI T1-weighted templates in stereotaxic space after spatial normalization. The bottom left of the figure shows lesion overlap between patients and a reconstruction of the 3-D probabilistic map (51% to 60%) of right and left dentate/interposed (D/I-N) cerebellar nuclei. The color code indicates the number of subjects whose lesions overlapped with D/I-N nuclei.

The macroscopic cerebellar damage in each patient was assessed after spatial normalization. The involvement of specific cerebellar structures was evaluated with the 3D MRI atlas of the human cerebellum [45] and the 3D MRI atlas of human cerebellar nuclei [46] . To detail the involvement of the nuclei, a 3D probabilistic map (51% to 60%) of right and left dentate/interposed cerebellar nuclei (D/I-N) [45] was reconstructed on a standard template using MRIcro, creating a ROI for the nuclei. Then, the patients' lesions and reconstruction of the nuclei were overlapped ( Figure 1 ).

Cerebellar lesions were first drawn on each patient's 3D MPRAGE images in native space using MRIcro ( www.sph.sc.edu/comd/rorden/mricro.html ), thus creating a region of interest (ROI) for each lesion and a corresponding lesion mask, smoothed to 8 mm full width at half maximum (FWHM) and a 0.001% threshold. The 3D MPRAGE images were processed using SPM2 ( www.fil.ion.ucl.ac.uk/spm ). For each FCb subject, images were reoriented manually according to the default template in SPM2 and normalized into the standard proportional stereotaxic space [Montreal Neurological Institute (MNI)] [44] .

Each participant performed 2 sessions; one session with the right and one session with the left arm. Each session included 5 blocks of CMT (80 trials each) and 1 block of GOT (60 trials each). The order in which each arm was used was balanced between subjects, and the GOT always preceded the CMT for each arm. To facilitate the subject's performance on the CMT, the starting SSD for each block was always set to the shortest option (17 ms). A rest period (minimum of 2 minutes) between blocks was allowed.

(A) Sequence of events in the go and stop trials for the Go_only (GOT) and countermanding (CMT) tasks. All trials started with the appearance of double vertical bars (fixation point; 2×11 pixels, separated by 2 pixels) in the middle of a screen. After a holding time (800–1200 ms), the central stimulus was replaced by an oriented arrow (Go signal; 12×12 pixels), indicating the direction of the movement. In the go trials (upper part), the subjects had to move the joystick toward the indicated direction as quickly as possible. The time between the Go signal and the onset of movement corresponded to the RT. In the stop trials (lower part), after a variable SSD, a central red square (Stop signal; 200×200 pixels) replaced the arrow, prompting the subjects to withhold the programmed movement and keep the joystick in the resting position. Trials with successfully suppressed movements are indicated as ‘cancelled’; trials with movements executed after a stop signal presentation are indicated as ‘not cancelled’. (B) Relationship among stop signal delay (SSD) duration and probability of error (pE). The longer is the SSD the higher is the pE. By assuming the go process identical in go and stop trials, the reaction time (RT) distribution, and the above relationship could be used to calculate the duration of the stop process (stop signal reaction time; SSRT; see text for details).

Subjects performed 2 versions of a joystick reaction time task ( Figure 2A ). In the GO_only task (GOT), participants moved the joystick in response to a directional go signal (go trials). In the Countermanding task (CMT), subjects responded to the go signal (CMT go trials), as in the GOT, but withheld the movement when, in 25% of the overall trials, a stop signal was presented (stop trials) after varying delays (stop signal delay; SSD). In both GOT and CMT the primary task's demand was of responding as quickly as possible to go signal presentation. If subject correctly reacted to the stop signal, the trial was considered canceled, and if the subject failed to stop the movement, the trial was considered not canceled ( Figure 2A ). When the RT exceeded 1 s in the go trials, the trial was aborted and the subject received an acoustic error feedback. Successfully performed go trials were signaled using different acoustic feedback. Canceled and not canceled stop trials were signaled with 2 acoustic stimuli. Another acoustic stimulus sounded when the RT exceeded 500 ms as a warning for the participant to respect the primary task's demand of responding as quickly as possible.

Behavioral data analysis

A common behavioural finding of the CMT is that the probability of error (pE; i.e., probability of not cancelling the movement) in stop trials increases with the length of the SSD (Figure 2B; white portion of RT distribution). According to the Logan's model [48], the duration of the stop process (stop signal reaction time; SSRT) could be estimated, in each subject, by using the go trials RT distribution and the pE observed for each SSD used. Since is well known that the SSRT estimate is more reliable when obtained with an SSD corresponding to a pE that approximates 0.5 [47], we used a staircase procedure to select the SSD in each stop trial. The SSD was increased by 50 ms after each successfully canceled stop trial and decreased by 50 ms after 2 consecutive not canceled stop trials. The procedure automatically adapts the SSD duration to a subject's performance to obtain a session's pE that approximates 0.5 and is similar between groups (for a similar approach, see [48]).

Figure 3 shows the sequence of consecutive SSDs (red and white diamonds dots) for a CMT session, as adapted by a staircase algorithm to the performance of a control subject in the example. In the right portion of the figure, black squares represent the so-called ‘inhibition function’ (i.e., the proportion of not canceled [pE] stop trials at each SSD). The proportion of various SSDs in the session is shown as a histogram, highlighting those that were presented more than 10 times. These SSDs have been used to compute the session's representative SSD (braked red line in Figure 3) and to compute the session's SSRT (see [49] for a similar approach). According to the Logan's model [50], the duration of the stop process (SSRT) could be estimated by integrating the CMT go trials RT distribution until the integral equals the observed proportion of not canceled trials (pE) corresponding to the representative SSD (integration method; [50]). We also used a second method to estimate the SSRT corresponding to the subtraction of the representative SSD from the CMT RT distribution's average value (mean subtraction method; [50]). The use of at least two methods is common to increase the reliability of SSRT [47,51]. In our study the two methods provided comparable estimates, as confirmed by the analysis reported in the results section. To be consistent with classical approaches, we computed an average value and use it for all comparisons performed.

PPT PowerPoint slide

PowerPoint slide PNG larger image

larger image TIFF original image Download: Figure 3. Stop trial sequence and inhibition function. Each block of CMT (for both arms) started with an SSD of 17 ms (1 unit of refresh rate); this delay (stop signal delay; SSD) was increased by 50 ms after each successfully canceled stop trial and decreased by 50 ms after 2 consecutive not canceled stop trials. For each block, red diamonds represent SSDs presented more than 10 times in the session. These SSDs have been used to compute the representative SSD (red interrupted line). Rightmost panel shows the subject's inhibition function (black squares and black solid lines); i.e., the relationship among SSD duration and probability of error (pE). The number of SSDs presented is reported as a histogram. Filled bars indicate SSDs presented more than 10 times. https://doi.org/10.1371/journal.pone.0085997.g003

Before comparing between groups or conditions, the inhibition function obtained for each subject has been normalized as previously described [50] to remove influences due to subject's differences in RT, SSD and SSRT. Thus, for each participant we computed the so-called standardized (z-score) relative finish time (ZRFT) [per the equation: ZRFT = (RT mean −SSD−SSRT)/RT SD , where RT mean and RT SD are the mean and standard deviation, respectively, of the RT in the go trials]. After this normalization, the slope of the inhibition function is believed to measure one's ability to trigger the stop process, regardless of the variability in RT in the go trials, the different values of SSDs used and the estimated value of SSRT [50]. In general, the slope of the inhibition function will be steeper when the inhibitory mechanism is more efficient.

We also computed a measure of the proactive control [52] and the monitoring of the response after each stop signal appearance in the trial sequence or not canceled (error) stop trial. For each subject, we computed post-stop correct and post-stop error slowing by subtracting the mean RT in the go trials after canceled and not canceled stop trials, respectively, from the mean RT in the go trials that were preceded and followed by a go trial (go-go-go sequence).

In FCb patients, we considered the functional arm to be the arm that was contralateral to the compromised cerebellar hemisphere and the hypofunctional arm as the one that was ipsilateral to it. In controls, the dominant and nondominant arms were considered equivalent to the functional and hypofunctional arms, respectively. This approach allows reducing the possibility that patients' impaired performances result statistically significant because of the comparison between controls' dominant arm and patients' affected arm (for a similar approach see [53]). Multifactorial analysis of variance (ANOVA) was used to test the significance of comparisons in RT and SSRT between patients and controls (or between tasks and arm used). Analysis of covariance (ANCOVA) was used to examine differences in the slope of the linear portion (0.15<pE<0.85) of the normalized inhibition function (ZRFT) between groups [54]. Post hoc contrast was conducted using Fisher LSD (for ANOVA) and Tukey-Kramer test (for ANCOVA) with Matlab's multicompare function.

We used an alpha level of 0.05 for all statistical tests. Thus, p values are reported in the text as exact values. However, p = 0.001 also include values of p<0.001. Similarly, when the software does not provide an exact p value, we indicate p<0.05.