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Keywords:

  • cognition;
  • compensatory mechanisms;
  • Huntington's disease;
  • P300;
  • SART

Abstract

  1. Top of page
  2. Abstract
  3. Background
  4. Method
  5. Results
  6. Discussion
  7. References

Background

Earlier research has found cross-sectional attentional control deficits in manifest Huntington's disease (HD) using neuropsychological testing combined with simultaneous P300 registration. In the current pilot-study, we investigate attentional control in pre-manifest and manifest HD over a 3-year follow-up period.

Method

Five manifest HD (MHD), 9 pre-manifest HD (PMHD), and 12 control subjects were included. Sustained Attention to Response task (SART) and P300 registration resulted in number of errors, reaction time (RT), and P300 amplitude and latency. RT change patterns surrounding No-go trials were also investigated. Within-subject differences were tested using paired-samples t-tests and between-group results with ANCOVA on delta scores (follow-up – baseline scores).

Results

Manifest HD made more errors and were slower than controls and PMHD. Longitudinally, MHD showed an overall RT increase and a specific slowing on trials preceding a correct No-go trial (within-group effects). The latter was also seen in PMHD. P300 latency prolongation was found for controls on No-go and for MHD on Go trials. On specific trials surrounding both correct and incorrect No-go trials, MHD became significantly slower over time than controls and PMHD (between-group effects).

Conclusions

Over 3-years, MHD subjects became slower on the SART and showed a prolongation of P300 latency on specific SART trials. Specific slowing of performance over time was also seen in PMHD, suggestive of compensatory mechanisms in this group.


Background

  1. Top of page
  2. Abstract
  3. Background
  4. Method
  5. Results
  6. Discussion
  7. References

Huntington's disease (HD) is a neurodegenerative disease caused by a gene mutation located on chromosome 4 (HDCRG, 1993). Its clinical manifestation is heterogeneous, with symptoms and signs occurring in three domains: motor, psychiatry, and cognition (Tabrizi et al., 2011).

Attentional deficits in HD patients have been widely demonstrated (Aron et al., 2003; Muller et al., 2002; Peavy et al., 2010). In pre-manifest HD subjects, i.e., gene carriers without overt clinical symptoms, differences in attentional processing compared with controls have also been found (Lawrence et al., 1998), but with inconsistent results (Campodonico, Codori & Brandt, 1996; Farrow et al., 2007). Reports on longitudinal change in attentional functioning in pre-manifest HD are few (Beglinger et al., 2010; Lemiere, Decruyenaere, Evers-Kiebooms, Vandenbussche & Dom, 2004; Verny et al., 2007), and again contradictory results have been found (Hart, Middelkoop, Jurgens, Witjes-Ane & Roos, 2011; Witjes-Ane et al., 2007).

A practical test to investigate attentional processing is the Sustained Attention to Response Task (SART; Robertson, Manly, Andrade, Baddeley & Yiend, 1997), a simple Go/No-go task with little motor involvement. The P300, an event-related potential (ERP) that can be deduced from the EEG, is proposed to be an electrophysiological substrate of attentional and inhibitory processes (Duncan et al., 2009; Kok, 1997). In combination, these two assessments have demonstrated ability to detect lapses in attention (Datta et al., 2007).

Hart et al. (2012) combined the SART with a simultaneous P300 registration to investigate attentional functioning in both a manifest and a pre-manifest HD (PMHD) group cross-sectionally. They demonstrated that attentional control was deficient in manifest HD subjects, apparent in the inability to directly resume task requirements after having made an error. The manifest subjects showed higher error rates corroborated by abnormalities in the P300 signal. While the attentional control deficit in manifest HD (MHD) was evident, the performance of the PMHD group did not differ from that of controls, and no P300 abnormalities were found.

Recent MRI studies reported early brain changes involving grey and white matter (van den Bogaard, Dumas, van der Grond, van Buchem & Roos, 2012; Bohanna, Georgiou-Karistianis, Hannan & Egan, 2008) in pre-manifest gene carriers even far from expected disease onset. This raises the possibility that these changes can also be measured with functional assessments, such as P300. Indeed, differences in ERPs between PMHD subjects and controls have been found (Nguyen, Bradshaw, Stout, Croft & Georgiou-Karistianis, 2010). A majority of these studies have found reduced neurophysiological measures in the absence of abnormal clinical performance in the pre-manifest groups. This coincides with findings in MRI studies where pathological changes in PMHD gene carriers are seen before onset of clinical symptoms (Bohanna et al., 2008)

To date, one longitudinal study has been performed using electrophysiological assessment in HD. Here, somatosensory-evoked potentials were studied in a group of MHD subjects. The amplitude of these potentials demonstrated progressive decline over the 2-year follow-up period (Ehle, Stewart, Lellelid & Leventhal, 1984). To our knowledge, no longitudinal electrophysiological research has been performed in PMHD subjects yet.

The current pilot study aimed to investigate attentional deficits in PMHD and MHD subjects longitudinally. Observed early brain changes in PMHD literature lead us to expect possible longitudinal change for SART error scores and P300 characteristics over the 3-year interval in this group. For the manifest group, we expected to find abnormalities similar to those found earlier by Hart and colleagues: longer reaction time, more errors, and a lower No-go P300 amplitude than controls and PMHD subjects. Furthermore, due to the progressive nature of HD, we expect a longitudinal worsening of these outcome values.

Method

  1. Top of page
  2. Abstract
  3. Background
  4. Method
  5. Results
  6. Discussion
  7. References

Participants

Five manifest (MHD), 10 pre-manifest (PMHD), and 13 control subjects participated in this pilot study and were tested with a 3-year interval using the same tests. All subjects completed the baseline and follow-up visit, with a mean follow-up time of 36.7 months. One PMHD and one control subject were excluded from longitudinal analyses due to excessive muscle artefacts visible during the ERP registration. Eventually, data of 5 MHD, 9 PMHD and 12 control subjects were analysed. None of the PMHD subjects converted to manifest HD over the study period. All subjects were grouped at visit 1 and were subsequently analysed in this group at follow-up.

All participants were recruited from our outpatient neurology clinic. The controls were gene-negative relatives. Gene carriers were considered ‘pre-manifest’ if they had a CAG repeat expansion of >39 and a total motor score (TMS) of ≤5 on the Unified Huntington's Disease Rating Scale (UHDRS; Huntington Study Group, 1996). Disease burden was calculated using the formula ‘age (CAG-35.5)’ (Penney, Vonsattel, MacDonald, Gusella & Myers, 1997). Exclusion criteria for all subjects were major psychiatric disorder, neurological co-morbidity, a score of ≤25 on the Mini Mental State Examination (MMSE; Folstein, Folstein & McHugh, 1975) and medication with known effects on the P300 (e.g., neuroleptics). The study was approved by the local medical ethical committee and all participants gave written informed consent (according to the declaration of Helsinki). Subjects underwent neurological examination including the complete UHDRS, P300 and SART assessment on both baseline (visit 1) and follow-up visit (visit 2). The MMSE was used to measure global cognitive functioning. Depression was measured with the depression part of the Problem Behaviours Assessment – short version (Craufurd, Thompson & Snowden, 2001), where depressive feelings are scored by severity and frequency (score range 0–16). The neurological assessment was performed at both visits by clinicians specialized in HD, blinded for genetic status.

Sustained Attention to Response Task

The SART was administered during both visits under the same conditions. Subjects were seated in a comfortable chair 1 m from a computer screen, with a computer keyboard placed in easy access of the dominant hand. Numbers from 1 to 9 were each shown 25 times on a computer screen. Subjects were asked to respond to every number by pressing a spacebar (‘Go’ trials), except when the number 3 was shown (‘No-go’ trials). In the case of a No-go trial, subjects were instructed to withhold their response. Accuracy and speed were instructed to be equally important. Before the test, subjects were allowed to practise with 25 random trials. The numbers were shown for 250 ms followed by a blank screen for 900 ms (Robertson et al., 1997). Reaction time (RT) was recorded whenever the spacebar was pressed. To ensure accurate measurement of RT, a cathode ray screen was used together with a purpose-built hardware device that allowed precise measurement of the build-up time of the screen information and hence of RT in relation to the visual stimulus (Hart et al., 2012).

Outcome measures for the SART were RT and number of errors. ‘Overall RT’ refers to mean RT over all trials performed. Errors are divided into total number of errors, and errors on Go and No-go trials. For error processing analyses, the mean RT of the trials directly preceding and directly following both correct and incorrect No-go trials were used (‘3’ is the No-go item in the SART). A delta score was also computed, which comprised the difference between the mean RT on the trials directly preceding and directly following both correct and incorrect (i.e., an incorrect response to a 3) No-go trials.

ERP recording and analysis

Twenty-one Ag/AgCl electrodes were placed according to the 10/20 convention. ECG, respiration, and horizontal eye movement leads were also recorded. The EEG was band-pass filtered from 0.16 to 70 Hz before display and analysis. Sample frequency was 200 Hz and A–D precision 12 bits. For the P300 analysis, we used the midline sites Fz (frontal), Cz (central), and Pz (parietal) with linked mastoids as reference. The computer controlling the SART paradigm wrote synchronization signals to the EEG machine, allowing averaging to take place offline after controlling for signal quality. Data were averaged over epochs of 1200 ms, starting 200 ms before stimulus onset. Individual trials with eye blink artefacts or suspected muscle artefacts were excluded from P300 analysis. The P300 component was defined as the maximum positivity between 350 and 650 ms. ERP analysis, including peak detection, was performed automatically using an in-house-developed program written in MATLAB (The MathWorks, Natick, MA, USA). Peak amplitudes were measured relative to a 200 ms baseline before stimulus onset. P300 outcome measures consisted of amplitude and latency data. The mean amplitudes and latencies for all trials, all Go trials, and all No-go trials were calculated (Hart et al., 2012).

Statistical analysis

Data analysis was performed using IBM SPSS statistics for Windows, version 20.0 (Armonk, NY, USA). Demographic variables were compared between groups using ANOVA (continuous variables) and Pearson's χ2 (categorical variables). Classification of the groups at baseline was used for all analyses. ANCOVA was performed for cross-sectional SART and P300 analyses at baseline. For SART error scores, the age, mean RT at time of visit and the baseline value of the tested variable were used as covariates. Age was chosen because of the known effect of ageing on neuropsychological testing. With the inclusion of RT as covariate, we assume to test more ‘pure’ cognitive performance, while controlling for possible differences in RT. Baseline scores were chosen as significant baseline differences emerged among the three groups. For the RT, P300, and error processing analyses, age at time of visit and the baseline value of the tested variable were selected as covariates. Again, age has been proven to have an altering effect on both RT and P300 characteristics. For longitudinal analyses of between-group effects, delta scores (follow-up visit score – baseline visit score) were calculated and analyses of covariance were performed on these scores. Age at baseline and baseline values of the tested variables were used as covariates, except for the analyses of SART error scores where age, mean RT at baseline, and baseline value of the tested variable were selected. Significant main results were further investigated using post-hoc tests. Within-subject effects were investigated using paired samples t-tests. Effect sizes are reported as partial eta-squared values. The level of statistical significance was set at p ≤ .05. Due to the explorative nature of this study, we chose to analyse the data making use of fairly straightforward tests such as ANCOVA on delta scores and paired samples t-tests. Therefore, also no correction for multiple testing was applied to maximize the chance of finding differences.

Results

  1. Top of page
  2. Abstract
  3. Background
  4. Method
  5. Results
  6. Discussion
  7. References

Demographic data

Demographic and clinical data of baseline and follow-up visits are shown in Table 1. The groups were similar in terms of age, gender, education, and total functional, depression, and MMSE scores on both visits. MHD subjects had a higher disease burden than PMHD subjects (F(1, 12) = 12.41, = .004). The TMS of the MHD group was higher than the TMS of the PMHD (F(2, 23) = 8.89, = .002) and control group (visit 1: F(2, 23) = 8.89, = .003, and visit 2: F(2, 23) = 8.89, < .001) on both visits.

Table 1. Descriptive statistics at baseline and follow-up visits
CharacteristicPre-manifest HD (n = 9)Manifest HD (n = 5)Controls (n = 12)
Note
  1. MMSE = Mini Mental State Examination; Data are presented as mean (SD).

  2. a

    Total number.

Age (years)   
Baseline40.3 (10.0)45.4 (10.7)48.2 (9.7)
Follow-up43.4 (9.7)48.4 (10.7)51.3 (9.7)
Gender, m/fa   
Baseline3/62/35/7
Education (years)   
Baseline12.3 (2.6)14.4 (2.9)11.9 (2.7)
CAG repeat length   
Baseline41.3 (1.5)44.4 (3.1)20.0 (2.9)
Disease burden   
Baseline232.2 (73.3)382.5 (82.5) 
Follow-up250.7 (75.8)409.2 (90.7) 
Total motor score (range 0–124)   
Baseline1.6 (2.5)6.4 (1.3)2.0 (2.2)
Follow-up2.2 (1.5)14.8 (7.7)3.0 (3.4)
Total functional capacity (range 0–13)   
Baseline12.2 (1.1)12.0 (1.4)13.0 (0)
Follow-up11.8 (1.6)12.0 (1.2)12.8 (0.6)
PBA-s depression score (range 0–16)   
Baseline2.8 (2.9)2.2 (3.3)3.0 (3.5)
Follow-up1.0 (2.1)2.0 (2.0)1.1 (1.6)
Score MMSE (range 0–30)   
Baseline28.8 (0.8)28.4 (0.9)29.0 (1.0)
Follow-up28.8 (1.2)28.6 (1.5)29.4 (0.7)

Cross-sectional data

Cross-sectional data of the SART and P300 are shown in Table 2. At baseline, MHD subjects made more total (F(2, 21) = 4.07, = .03, ηp2 = 0.280) and No-go errors (F(2, 21) = 5.18, = .02, ηp2 = 0.330) compared with PMHD subjects and controls.

Table 2. SART and P300 data: Cross-sectional and longitudinal within-subject and between-group analyses
 GroupBaselineFollow-upp-values
Cross-sectional analyses baselineLongitudinal within-subject analysesaLongitudinal between-group analysesb
Note
  1. SART = Sustained Attention to Response Task; PMHD = Pre-manifest HD (= 9); MHD = Manifest HD (= 5); Controls (n = 12); RT = reaction time in milliseconds. Data are presented as mean (SD). Amplitude is in microvolts (μV). Latency is in milliseconds. Bold values are statistically significant at p < 0.05.

  2. aPaired samples t-tests. bANCOVA on delta-scores.

SART      
Total errorsPMHD7.9 (4)6.7 (3) .03 0.171.092
MHD12.0 (8)12.4 (4)0.889
Controls8.2 (5)9.3 (3)0.362
No-go errorsPMHD6.9 (3)6.4 (3) .02 0.5590.127
MHD10.8 (7)8.8 (4)0.417
Controls7.1 (4)8.3 (3)0.2034
Go errorsPMHD1.0 (2)0.2 (0)0.5960.2110.134
MHD1.2 (2)3.6 (4)0.170
Controls1.1 (1)0.9 (1)0.732
Mean RTPMHD361.4 (32)374.9 (33).055.098 .01
.01
MHD422.9 (81)481.8 (84)
Controls371.2 (29)379.9 (39)0.435
P300      
LatencyPMHD380 (18)394 (36) .04 0.1380.720
MHD435 (46)451 (58)0.313
Controls406 (39)413 (39)0.407
Latency No-goPMHD391 (34)420 (47) .02 .0800.567
MHD449 (62)474 (45)0.453
Controls408 (22)432 (33) .004
Latency GoPMHD375 (21)396 (36) .04 0.1190.133
MHD430 (45)454 (53) .05
Controls409 (41)406 (30)0.646
AmplitudePMHD10.2 (5)9.6 (4)0.4270.5970.939
MHD7.8 (3)8.2 (2)0.630
Controls9.6 (3)8.9 (3)0.222
Amplitude No-goPMHD17.3 (6)16.5 (5) .04 0.5340.466
MHD10.9 (3)14.1 (6)0.223
Controls17.8 (4)17.6 (5)0.742
Amplitude GoPMHD9.6 (5)9.1 (5)0.4490.6280.931
MHD7.6 (3)7.8 (2)0.769
Controls8.3 (3)7.9 (3)0.221

Concerning the P300 characteristics, MHD subjects showed a longer overall (F(2, 22) = 3.68, = .04, ηp2 = 0.250), Go (F(2, 22) = 3.53, = .047, ηp2 = 0.243) and No-go (F(2, 22) = 4.64, = .02, ηp2 = 0.297) latency than PMHD and control subjects. Also, the MHD group demonstrated a lower No-go amplitude than the control group (F(2, 22) = 3.69, = .04, ηp2 = 0.251).

Longitudinal data

Between-group effects were found longitudinally only for the SART mean RT. Here, all groups became slower over time, but the MHD group significantly more compared with both PMHD and control subjects (F(2, 21) = 5.61, = .01, ηp2 = 0.348). Concerning within-subject differences, paired sample t-tests showed a significant mean RT increase over time on the SART for MHD participants (t(4) = −9,56, = .01, ηp2 = 0.938).

A prolongation of the No-go P300 latency was found for controls (t(11 = −3.56, = .004, ηp2 = 0.494) and of the Go latency for MHD (t(4) = −2.82, = .048, ηp2 = 0.570). No significant changes were observed concerning P300 amplitude.

SART error processing analyses – cross-sectional data

Data for the error processing analysis are shown in Table 3. Cross-sectionally, MHD subjects reacted slower on the trial directly following both correctly (F(2, 22) = 3.75, = .04, ηp2 = 0.254) and incorrectly (F(2, 21) = 5.49, = .01, ηp2 = 0.343) withheld responses to No-go trials (appearance of the number ‘3’) compared with controls at baseline.

Table 3. SART error analysis data: Cross-sectional and longitudinal within-subject and between-group analyses
 GroupBaselineFollow-upp-values
Cross-sectional analyses baselineLongitudinal within-subject analysesaLongitudinal between-group analysesb
Note
  1. SART = Sustained Attention to Response Task; PMHD = Pre-manifest HD (= 9); MHD = Manifest HD (= 5); Controls (n = 12). Data are mean (SD). Reaction times are milliseconds. Bold values are statistically significant at p < 0.05.

  2. aPaired samples t-tests. bANCOVA on delta-scores.

Correct 3      
Reaction time before correct 3PMHD366 (21)392 (43).070 .03 .01
MHD426 (92)535 (128) .007
Controls409 (43)416 (67)0.760
Reaction time after correct 3PMHD314 (57)349 (37) .04 .054.003
MHD381 (76)421 (70)0.223
Controls317 (18)310 (23)0.442
Incorrect 3      
Reaction time before incorrect 3PMHD338 (45)350 (48)0.7770.3910.136
0.278
MHD350 (39)444 (194)
Controls349 (35)364 (53)0.625
Reaction time after incorrect 3PMHD414 (85)360 (36) .01 .092.001
MHD476 (104)529 (108)0.435
Controls338 (54)363 (59)0.414

SART error processing analyses – longitudinal data

ANCOVA on delta scores revealed several between-group differences over the 3-year follow-up period. For trials preceding a correct No-go trial, RT became longer over time in all groups, but MHD subjects became significantly more so than the other groups (F(2, 21) = 5.67, = .01, ηp2 = 0.351). On trials directly following a correctly responded No-go trial, the MHD group again showed a significant slowing in RT compared with controls (F(2, 21) = 7.78, = .003, ηp2 = 0.426). The latter group even showed a slight improvement in RT over time. Lastly, on trials directly following an incorrect No-go trial, the MHD differed from both controls and the PMHD group (F(2, 20) = 9.99, = .001, ηp2 = 0.500). Over time, the control group showed a slowing in RT, but the slowing of the MHD group was larger. The PMHD group even showed a substantial improvement in RT over time.

Regarding within-subject effects, paired sample t-tests showed that both MHD (t(4) = −5.15, = .007, ηp2 = 0.815) and PMHD (t(8) = −2.68, = .03, ηp2 = 0.418) participants became slower over time on trials directly preceding correct No-go trials.

Discussion

  1. Top of page
  2. Abstract
  3. Background
  4. Method
  5. Results
  6. Discussion
  7. References

In this pilot-study, we present preliminary data on longitudinal SART and simultaneous P300 assessment in HD. To our knowledge, we are the first to perform a longitudinal ERP study in pre-manifest HD. We found that over a course of 3 years, MHD subjects showed an increase in RT on the SART, and exhibited a prolongation of the P300 latency on specific trials of the SART. PMHD subjects only showed specific increase in reaction time just before having prevented a possible error on the SART.

In the MHD group, we replicated the findings of the cross-sectional study by Hart et al. (2012) on the SART and P300 in HD where MHD subjects make more errors on the SART than both other groups, and took longer to react to the trials (follow-up visit). The increase in reaction time of the patients compared with the other two groups is not surprising, and is likely to reflect motor slowing. This conclusion is strengthened by only specific, and not overall, RT increase in the PMHD group. In the earlier study, the authors hypothesized that the observed slowing could reflect a speed-accuracy trade-off, a (conscious or unconscious) strategy applied by MHD participants to maintain task requirements (Samavatyan & Leth-Steensen, 2009). The increase in RT seen in the current MHD cohort does not, however, prevent these subjects from making more mistakes than the other two groups. So, there is no task-related benefit from the motor slowing. One explanation for this absence of benefit could be that the employment of the speed-accuracy trade-off has reached a maximum. If this level is reached, the impairment can no longer be compensated and task-related benefit is absent.

Longitudinally, the increase in RT of the MHD group was also significantly larger than the slowing of the PMHD and control subjects, which was expected in view of the neurodegenerative nature of HD. Neurodegeneration is also reflected in the neurophysiological data, as demonstrated by the cross-sectionally longer P300 latencies compared with the other groups, and the latency prolongation over time on Go trials. The P300 latency has been linked to stimulus evaluation time, or generalized, cognitive processing speed (Polich & Criado, 2006), so a lengthened latency in the MHD group could reflect reduced processing speed. Deficits in processing speed have also been demonstrated by other authors using other paradigms (Duff et al., 2010; Maroof, Gross & Brandt, 2011).

The significant post-error slowing for the MHD group that was found in the previous cross-sectional study was again observed in the present study. However, in the current analyses, it was not a specific finding, as slowing over the 3-year follow-up period was also found for trials directly preceding and following a trial where the response was correctly withheld to the appearance of the number 3. These findings most likely reflect the general motor slowing in patients that was already discussed, rather than specific cognitive slowing in response to being confronted with a No-go trial.

Cross-sectionally, pre-manifest subjects perform equally to control subjects, evidenced by the lack of cross-sectional results. Interestingly, in the PMHD group, we did find specific slowing over time. During follow-up, this group became slower in reacting to trials directly preceding correct No-go trials (i.e., correctly withholding the response to the appearance of ‘3’). This slowing was also seen in the MHD group, but only MHD subjects produced more errors than controls. The exact significance of such specific deterioration is difficult to explain, but as the PMHD subjects make the same number of errors as controls and increase in RT where controls do not, this could mean that it takes more attentional demands for PMHD subjects to maintain task performance. As PMHD subjects can keep with the demands of the SART, it could mean that the RT increase is the result of some kind of compensatory mechanism. That it reflects pure motor slowing is less likely as in this case we would have expected increased RT on more variables.

A candidate compensatory mechanism here could be speed-accuracy trade-off, a strategy that was used by MHD subjects in our cross-sectional study (Hart et al., 2012). That growing attentional demands could translate into increased RT is well described in speed-accuracy trade-off literature (Samavatyan & Leth-Steensen, 2009). Additionally, the controls did not slow over time on these specific trials, and produced a similar amount of errors as the PMHD subjects. This strengthens our hypothesis that some kind of compensation is utilized by the latter group. This proof of early compensation by means of speed-accuracy trade-off in PMHD complements our earlier hypothesis that in the current MHD cohort, the maximum level of compensation (by means of speed-accuracy trade-off) is reached and no more task-related benefits are observed.

That compensatory mechanisms are at work in PMHD has been suggested before (Feigin et al., 2006). In another basal ganglia disorder, Parkinson's disease (PD), compensatory mechanisms responsible for delaying overt symptom onset have long been accepted (Zigmond, Abercrombie, Berger, Grace & Stricker, 1990). Here, even several compensatory networks have been identified postponing the final appearance of parkinsonism (Bezard, Gross & Brotchie, 2003). Looking at our overall raw data, we also see that for SART errors and mean RT scores, the pre-manifest subjects perform better not only than the MHD, but also than the control subjects. This could reflect overall compensation to perform at pre-disease level.

As our preliminary data derived from small pilot groups, our conclusions should be considered with caution. Generalization of our results is limited as, due to the sample sizes, statistical power is low. Also, individual fluctuations in such a small sample could have large effects, especially in the MHD group, which consisted of 5 subjects. This is evident in the differences in RT patterns surrounding incorrect responses to a No-go trial, where, at baseline, some post-error slowing was visible (albeit not statistically significant) for MHD and PMHD, while it was absent at follow-up.

The combination of cognitive testing (SART) with simultaneous P300 registration is a strength of this study, in the way that the P300 is independent of motor slowing whereby conclusions about cognitive functioning can be made more easily. Following the specific result in the PMHD group, we recommend replication of this pilot study with larger numbers of participants to be better able to understand the transition from pre-manifest to manifest HD.

In conclusion, this pilot study partly replicated the findings from the cross-sectional study by Hart et al. (2012) that MHD subjects perform worse than both PMHD and control subjects on tests of attentional control. MHD subjects are slower and make more mistakes on the SART, and show longer P300 latencies. Longitudinal change in attentional control was observed for specific trials in the PMHD subjects, which could be suggestive of compensatory mechanisms in this phase of HD.

References

  1. Top of page
  2. Abstract
  3. Background
  4. Method
  5. Results
  6. Discussion
  7. References