Using Smartphone Sensors for Ataxia Trials: Consensus Guidance by the Ataxia Global Initiative Working Group on Digital-Motor Biomarkers

Smartphone sensors are used increasingly in the assessment of ataxias. To date, there is no specific consensus guidance regarding a priority set of smartphone sensor measurements, or standard assessment criteria that are appropriate for clinical trials. As part of the Ataxia Global Initiative Digital-Motor Biomarkers Working Group (AGI WG4), aimed at evaluating key ataxia clinical domains (gait/posture, upper limb, speech and oculomotor assessments), we provide consensus guidance for use of internal smartphone sensors to assess key domains. Guidance was developed by means of a literature review and a two stage Delphi study conducted by an Expert panel, which surveyed members of AGI WG4, representing clinical, research, industry and patient-led experts, and consensus meetings by the Expert panel to agree on standard criteria and map current literature to these criteria. Seven publications were identified that investigated ataxias using internal smartphone sensors. The Delphi 1 survey ascertained current practice, and systems in use or under development. Wide variations in smartphones sensor use for assessing ataxia were identified. The Delphi 2 survey identified seven measures that were strongly endorsed as priorities in assessing 3/4 domains, namely gait/posture, upper limb, and speech performance. The Expert panel recommended 15 standard criteria to be fulfilled in studies. Evaluation of current literature revealed that none of the studies met all criteria, with most being early-phase validation studies. Our guidance highlights the importance of consensus, identifies priority measures and standard criteria, and will encourage further research into the use of internal smartphone sensors to measure ataxia digital-motor biomarkers.

Quantitative Oculomotor Assessment in Hereditary Ataxia: Systematic Review and Consensus by the Ataxia Global Initiative Working Group on Digital-motor Biomarkers

Oculomotor deficits are common in hereditary ataxia, but disproportionally neglected in clinical ataxia scales and as outcome measures for interventional trials. Quantitative assessment of oculomotor function has become increasingly available and thus applicable in multicenter trials and offers the opportunity to capture severity and progression of oculomotor impairment in a sensitive and reliable manner. In this consensus paper of the Ataxia Global Initiative Working Group On Digital Oculomotor Biomarkers, based on a systematic literature review, we propose harmonized methodology and measurement parameters for the quantitative assessment of oculomotor function in natural-history studies and clinical trials in hereditary ataxia. MEDLINE was searched for articles reporting on oculomotor/vestibular properties in ataxia patients and a study-tailored quality-assessment was performed. One-hundred-and-seventeen articles reporting on subjects with genetically confirmed (n=1134) or suspected hereditary ataxia (n=198), and degenerative ataxias with sporadic presentation (n=480) were included and subject to data extraction. Based on robust discrimination from controls, correlation with disease-severity, sensitivity to change, and feasibility in international multicenter settings as prerequisite for clinical trials, we prioritize a core-set of five eye-movement types: (i) pursuit eye movements, (ii) saccadic eye movements, (iii) fixation, (iv) eccentric gaze holding, and (v) rotational vestibulo-ocular reflex. We provide detailed guidelines for their acquisition, and recommendations on the quantitative parameters to extract. Limitations include low study quality, heterogeneity in patient populations, and lack of longitudinal studies. Standardization of quantitative oculomotor assessments will facilitate their implementation, interpretation, and validation in clinical trials, and ultimately advance our understanding of the evolution of oculomotor network dysfunction in hereditary ataxias.

Differential effects of bilateral hippocampal CA3 damage on the implicit learning and recognition of complex event sequences

Learning regularities in the environment is a fundament of human cognition, which is supported by a network of brain regions that include the hippocampus. In two experiments, we assessed the effects of selective bilateral damage to human hippocampal subregion CA3, which was associated with autobiographical episodic amnesia extending ~50 years prior to the damage, on the ability to recognize complex, deterministic event sequences presented either in a spatial or a non-spatial configuration. In contrast to findings from related paradigms, modalities, and homologue species, hippocampal damage did not preclude recognition memory for an event sequence studied and tested at four spatial locations, whereas recognition memory for an event sequence presented at a single location was at chance. In two additional experiments, recognition memory for novel single-items was intact, whereas the ability to recognize novel single-items in a different location from that presented at study was at chance. The results are at variance with a general role of the hippocampus in the learning and recognition of complex event sequences based on non-adjacent spatial and temporal dependencies. We discuss the impact of the results on established theoretical accounts of the hippocampal contributions to implicit sequence learning and episodic memory.

Quantitative Oculomotor Assessment in Hereditary Ataxia: Discriminatory Power, Correlation with Severity Measures, and Recommended Parameters for Specific Genotypes

Characterizing bedside oculomotor deficits is a critical factor in defining the clinical presentation of hereditary ataxias. Quantitative assessments are increasingly available and have significant advantages, including comparability over time, reduced examiner dependency, and sensitivity to subtle changes. To delineate the potential of quantitative oculomotor assessments as digital-motor outcome measures for clinical trials in ataxia, we searched MEDLINE for articles reporting on quantitative eye movement recordings in genetically confirmed or suspected hereditary ataxias, asking which paradigms are most promising for capturing disease progression and treatment response. Eighty-nine manuscripts identified reported on 1541 patients, including spinocerebellar ataxias (SCA2, n = 421), SCA3 (n = 268), SCA6 (n = 117), other SCAs (n = 97), Friedreich ataxia (FRDA, n = 178), Niemann-Pick disease type C (NPC, n = 57), and ataxia-telangiectasia (n = 85) as largest cohorts. Whereas most studies reported discriminatory power of oculomotor assessments in diagnostics, few explored their value for monitoring genotype-specific disease progression (n = 2; SCA2) or treatment response (n = 8; SCA2, FRDA, NPC, ataxia-telangiectasia, episodic-ataxia 4). Oculomotor parameters correlated with disease severity measures including clinical scores (n = 18 studies (SARA: n = 9)), chronological measures (e.g., age, disease duration, time-to-symptom onset; n = 17), genetic stratification (n = 9), and imaging measures of atrophy (n = 5). Recurrent correlations across many ataxias (SCA2/3/17, FRDA, NPC) suggest saccadic eye movements as potentially generic quantitative oculomotor outcome. Recommendation of other paradigms was limited by the scarcity of cross-validating correlations, except saccadic intrusions (FRDA), pursuit eye movements (SCA17), and quantitative head-impulse testing (SCA3/6). This work aids in understanding the current knowledge of quantitative oculomotor parameters in hereditary ataxias, and identifies gaps for validation as potential trial outcome measures in specific ataxia genotypes.

Eye movements in Parkinson's disease: from neurophysiological mechanisms to diagnostic tools

Movement disorders such as Parkinson's disease (PD) impact oculomotor function - the ability to move the eyes accurately and purposefully to serve a multitude of sensory, cognitive, and secondary motor tasks. Decades of neurophysiological research in monkeys and behavioral studies in humans have characterized the neural basis of healthy oculomotor control. This review links eye movement abnormalities in persons living with PD to the underlying neurophysiological mechanisms and pathways. Building on this foundation, we highlight recent progress in using eye movements to gauge symptom severity, assess treatment effects, and serve as potential precision biomarkers. We conclude that whereas eye movements provide insights into PD mechanisms, based on current evidence they appear to lack sufficient sensitivity and specificity to serve as a standalone diagnostic tool. Their full potential may be realized when combined with other disease indicators in big datasets.

Retinal Optical Coherence Tomography Features Associated With Incident and Prevalent Parkinson Disease

BACKGROUND AND OBJECTIVES

Cadaveric studies have shown disease-related neurodegeneration and other morphological abnormalities in the retina of individuals with Parkinson disease (PD); however, it remains unclear whether this can be reliably detected with in vivo imaging. We investigated inner retinal anatomy, measured using optical coherence tomography (OCT), in prevalent PD and subsequently assessed the association of these markers with the development of PD using a prospective research cohort.

METHODS

This cross-sectional analysis used data from 2 studies. For the detection of retinal markers in prevalent PD, we used data from AlzEye, a retrospective cohort of 154,830 patients aged 40 years and older attending secondary care ophthalmic hospitals in London, United Kingdom, between 2008 and 2018. For the evaluation of retinal markers in incident PD, we used data from UK Biobank, a prospective population-based cohort where 67,311 volunteers aged 40-69 years were recruited between 2006 and 2010 and underwent retinal imaging. Macular retinal nerve fiber layer (mRNFL), ganglion cell-inner plexiform layer (GCIPL), and inner nuclear layer (INL) thicknesses were extracted from fovea-centered OCT. Linear mixed-effects models were fitted to examine the association between prevalent PD and retinal thicknesses. Hazard ratios for the association between time to PD diagnosis and retinal thicknesses were estimated using frailty models.

RESULTS

Within the AlzEye cohort, there were 700 individuals with prevalent PD and 105,770 controls (mean age 65.5 ± 13.5 years, 51.7% female). Individuals with prevalent PD had thinner GCIPL (-2.12 μm, 95% CI -3.17 to -1.07, p = 8.2 × 10-5) and INL (-0.99 μm, 95% CI -1.52 to -0.47, p = 2.1 × 10-4). The UK Biobank included 50,405 participants (mean age 56.1 ± 8.2 years, 54.7% female), of whom 53 developed PD at a mean of 2,653 ± 851 days. Thinner GCIPL (hazard ratio [HR] 0.62 per SD increase, 95% CI 0.46-0.84, p = 0.002) and thinner INL (HR 0.70, 95% CI 0.51-0.96, p = 0.026) were also associated with incident PD.

DISCUSSION

Individuals with PD have reduced thickness of the INL and GCIPL of the retina. Involvement of these layers several years before clinical presentation highlight a potential role for retinal imaging for at-risk stratification of PD.

Identification of motor progression in Parkinson's disease using wearable sensors and machine learning

Wearable devices offer the potential to track motor symptoms in neurological disorders. Kinematic data used together with machine learning algorithms can accurately identify people living with movement disorders and the severity of their motor symptoms. In this study we aimed to establish whether a combination of wearable sensor data and machine learning algorithms with automatic feature selection can estimate the clinical rating scale and whether it is possible to monitor the motor symptom progression longitudinally, for people with Parkinson's Disease. Seventy-four patients visited the lab seven times at 3-month intervals. Their walking (2-minutes) and postural sway (30-seconds,eyes-closed) were recorded using six Inertial Measurement Unit sensors. Simple linear regression and Random Forest algorithms were utilised together with different routines of automatic feature selection or factorisation, resulting in seven different machine learning algorithms to estimate the clinical rating scale (Movement Disorder Society- Unified Parkinson's Disease Rating Scale part III; MDS-UPDRS-III). Twenty-nine features were found to significantly progress with time at group level. The Random Forest model revealed the most accurate estimation of the MDS-UPDRS-III among the seven models. The model estimations detected a statistically significant progression of the motor symptoms within 15 months when compared to the first visit, whereas the MDS-UPDRS-III did not capture any change. Wearable sensors and machine learning can track the motor symptom progression in people with PD better than the conventionally used clinical rating scales. The methods described in this study can be utilised complimentary to the clinical rating scales to improve the diagnostic and prognostic accuracy.

Antiparkinsonian medication masks motor signal progression in de novo patients

Patients not yet receiving medication provide insight to drug-naïve early physiology of Parkinson's Disease (PD). Wearable sensors can measure changes in motor features before and after introduction of antiparkinsonian medication. We aimed to identify features of upper limb bradykinesia, postural stability, and gait that measurably progress in de novo PD patients prior to the start of medication, and determine whether these features remain sensitive to progression in the period after commencement of antiparkinsonian medication. Upper limb motion was measured using an inertial sensor worn on a finger, while postural stability and gait were recorded using an array of six wearable sensors. Patients were tested over nine visits at three monthly intervals. The timepoint of start of medication was noted. Three upper limb bradykinetic features (finger tapping speed, pronation supination speed, and pronation supination amplitude) and three gait features (gait speed, arm range of motion, duration of stance phase) were found to progress in unmedicated early-stage PD patients. In all features, progression was masked after the start of medication. Commencing antiparkinsonian medication is known to lead to masking of progression signals in clinical measures in de novo PD patients. In this study, we show that this effect is also observed with digital measures of bradykinetic and gait motor features.

Deep Brain Stimulation and Levodopa Affect Gait Variability in Parkinson Disease Differently

BACKGROUND

Both dopaminergic medication and subthalamic nucleus (STN) deep brain stimulation (DBS) can improve the amplitude and speed of gait in Parkinson disease (PD), but relatively little is known about their comparative effects on gait variability. Gait irregularity has been linked to the degeneration of cholinergic neurons in the pedunculopontine nucleus (PPN).

OBJECTIVES

The STN and PPN have reciprocal connections, and we hypothesized that STN DBS might improve gait variability by modulating PPN function. Dopaminergic medication should not do this, and we therefore sought to compare the effects of medication and STN DBS on gait variability.

MATERIALS AND METHODS

We studied 11 patients with STN DBS systems on and off with no alteration to their medication, and 15 patients with PD without DBS systems on and off medication. Participants walked for two minutes in each state, wearing six inertial measurement units. Variability has previously often been expressed in terms of SD or coefficient of variation over a testing session, but these measures conflate long-term variability (eg, gradual slowing, which is not necessarily pathological) with short-term variability (true irregularity). We used Poincaré analysis to separate the short- and long-term variability.

RESULTS

DBS decreased short-term variability in lower limb gait parameters, whereas medication did not have this effect. In contrast, STN DBS had no effect on arm swing and trunk motion variability, whereas medication increased them, without obvious dyskinesia.

CONCLUSIONS

Our results suggest that STN DBS acts through a nondopaminergic mechanism to reduce gait variability. We believe that the most likely explanation is the retrograde activation of cholinergic PPN projection neurons.

Longitudinal Monitoring of Progressive Supranuclear Palsy using Body-Worn Movement Sensors

BACKGROUND

We have previously shown that wearable technology and machine learning techniques can accurately discriminate between progressive supranuclear palsy (PSP), Parkinson's disease, and healthy controls. To date these techniques have not been applied in longitudinal studies of disease progression in PSP.

OBJECTIVES

We aimed to establish whether data collected by a body-worn inertial measurement unit (IMU) network could predict clinical rating scale scores in PSP and whether it could be used to track disease progression.

METHODS

We studied gait and postural stability in 17 participants with PSP over five visits at 3-month intervals. Participants performed a 2-minute walk and an assessment of postural stability by standing for 30 seconds with their eyes closed, while wearing an array of six IMUs.

RESULTS

Thirty-two gait and posture features were identified, which progressed significantly with time. A simple linear regression model incorporating the three features with the clearest progression pattern was able to detect statistically significant progression 3 months in advance of the clinical scores. A more complex linear regression and a random forest approach did not improve on this.

CONCLUSIONS

The reduced variability of the models, in comparison to clinical rating scales, allows a significant change in disease status from baseline to be observed at an earlier stage. The current study sheds light on the individual features that are important in tracking disease progression. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Parkinson’s disease deficits in time perception to auditory as well as visual stimuli – A large online study

Cognitive deficits are common in Parkinson’s disease (PD) and range from mild cognitive impairment to dementia, often dramatically reducing quality of life. Physiological models have shown that attention and memory are predicated on the brain’s ability to process time. Perception has been shown to be increased or decreased by activation or deactivation of dopaminergic neurons respectively. Here we investigate differences in time perception between patients with PD and healthy controls. We have measured differences in sub-second- and second-time intervals. Sensitivity and error in perception as well as the response times are calculated. Additionally, we investigated intra-individual response variability and the effect of participant devices on both reaction time and sensitivity. Patients with PD have impaired sensitivity in discriminating between durations of both visual and auditory stimuli compared to healthy controls. Though initially designed as an in-person study, because of the pandemic the experiment was adapted into an online study. This adaptation provided a unique opportunity to enroll a larger number of international participants and use this study to evaluate the feasibility of future virtual studies focused on cognitive impairment. To our knowledge this is the only time perception study, focusing on PD, which measures the differences in perception using both auditory and visual stimuli. The cohort involved is the largest to date, comprising over 800 participants.

High-sensitivity troponin (hs-cTn) for cardiovascular risk prognostication: a systematic review and meta-analysis

Background

Chronic low-grade inflammation is involved in coronary atherosclerosis progression whereas recent research efforts suggest that preventative methods should be tailored to the “residual inflammatory risk”. As such, modalities for the early identification of the risk have to be investigated.

Methods

We performed a systematic review and meta-analysis according to the PRISMA guidelines. Any study that presented the prognostic value of high sensitivity troponin (hs-cTn) of vascular inflammation in stable patients without known cardiac heart disease was considered to be potentially eligible. The Medline (PubMed) database was searched up to April 22, 2021. The main endpoint was the difference in c-index (Δ[c-index]) with the use of hs-cTn for major adverse cardiovascular events (MACEs), cardiovascular and all-cause mortality. We calculated I2 to test heterogeneity.

Results

In total, 44 studies and 112,288 stable patients without known coronary heart disease were included in this meta-analysis. The mean follow-up duration of the whole cohort was 6.8±1.1 years. 77,004 (68.5%) of the patients presented in low cardiovascular risk while 35,284 (31.5%) in high. The overall pooled estimated of Δ[c-index] for MACE was 1.4% (95% CI: 0.7–2.1, I2=0%) and for cardiovascular death 1.3% (95% CI: 0.3–2.3, I2=0%). Finally, the overall pooled estimate of Δ[c-index] for all-cause mortality was 3% (95% CI: 1.9–3.9, I2=86%), while high heterogeneity was observed between the studies.

Conclusion

The predictive usefulness of changes in hs-cTn measures in stable individuals with either high or low cardiovascular risk, demonstrating that assessing vascular inflammation in addition to clinical risk factors enhances risk prediction for cardiovascular events and all-cause mortality. Further prospective studies are necessary to confirm these findings and assist clinical decision-making regarding the most optimal prevention strategy.

Funding Acknowledgement

Type of funding sources: None.

Oculomotor deficits in Parkinson's disease: Increasing sensitivity using multivariate approaches

Parkinson's disease (PD) affects several domains of neurological function, from lower-level motor programs to higher cognitive processing. As certain types of eye movements (saccades) are fast, non-fatiguing, and can be measured objectively and non-invasively, they are a promising candidate for quantifying motor and cognitive dysfunction in PD, as well as other movement disorders. In this pilot study, we evaluate the latency (reaction time), damping (resistance to oscillation), and amplitude of saccadic movements in two tasks performed by 25 PD patients with mild to moderate disease and 26 age-matched healthy controls. As well as general increases in reaction time caused by PD, the damping of saccadic eye movements was found to be task-dependent and affected by disease. Finally, we introduce a proof-of-concept multivariate model to demonstrate how information from saccadometry can be combined to infer disease status.

Longitudinal changes of early motor and cognitive symptoms in progressive supranuclear palsy: the OxQUIP study

BACKGROUND

Progressive supranuclear palsy (PSP) is a rare neurodegenerative condition characterised by a range of motor and cognitive symptoms. Very little is known about the longitudinal change in these symptoms over time. Moreover, the effectiveness of clinical scales to detect early changes in PSP is still a matter of debate.

OBJECTIVE

We aimed to determine longitudinal changes in PSP features using multiple closely spaced follow-up time points over a period of 2 years. Methods 28 healthy control and 28 PSP participants, with average time since onset of symptoms of 1.9 years, were prospectively studied every 3 months for up to 24 months. Changes from baseline scores were calculated at each follow-up time point using multiple clinical scales to identify longitudinal progression of motor and cognitive symptoms.

RESULTS

The Montreal Cognitive Assessment, but not the Mini-Mental State Examination, detected cognitive decline at baseline. Both scales revealed poor longitudinal sensitivity to clinical change in global cognitive symptoms. Conversely, the Movement Disorders Society Unified Parkinson's disease Rating Scale - part III and the PSP Rating Scale (PSPRS) reliably detected motor decline less than 2 years after disease onset. The 'Gait/Midline' PSPRS subscore consistently declined over time, with the earliest change being observed 6 months after baseline assessment.

CONCLUSION

While better cognitive screening tools are still needed to monitor cognitive decline in PSP, motor decline is consistently captured by clinical rating scales. These results support the inclusion of multiple follow-up time points in longitudinal studies in the early stages of PSP.

Discriminating progressive supranuclear palsy from Parkinson's disease using wearable technology and machine learning

BACKGROUND

Progressive supranuclear palsy (PSP), a neurodegenerative conditions may be difficult to discriminate clinically from idiopathic Parkinson's disease (PD). It is critical that we are able to do this accurately and as early as possible in order that future disease modifying therapies for PSP may be deployed at a stage when they are likely to have maximal benefit. Analysis of gait and related tasks is one possible means of discrimination.

RESEARCH QUESTION

Here we investigate a wearable sensor array coupled with machine learning approaches as a means of disease classification.

METHODS

21 participants with PSP, 20 with PD, and 39 healthy control (HC) subjects performed a two minute walk, static sway test, and timed up-and-go task, while wearing an array of six inertial measurement units. The data were analysed to determine what features discriminated PSP from PD and PSP from HC. Two machine learning algorithms were applied, Logistic Regression (LR) and Random Forest (RF).

RESULTS

17 features were identified in the combined dataset that contained independent information. The RF classifier outperformed the LR classifier, and allowed discrimination of PSP from PD with 86 % sensitivity and 90 % specificity, and PSP from HC with 90 % sensitivity and 97 % specificity. Using data from the single lumbar sensor only resulted in only a modest reduction in classification accuracy, which could be restored using 3 sensors (lumbar, right arm and foot). However for maximum specificity the full six sensor array was needed.

SIGNIFICANCE

A wearable sensor array coupled with machine learning methods can accurately discriminate PSP from PD. Choice of array complexity depends on context; for diagnostic purposes a high specificity is needed suggesting the more complete array is advantageous, while for subsequent disease tracking a simpler system may suffice.

Quantifying Motor Impairment in Movement Disorders

Until recently the assessment of many movement disorders has relied on clinical rating scales that despite careful design are inherently subjective and non-linear. This makes accurate and truly observer-independent quantification difficult and limits the use of sensitive parametric statistical methods. At last, devices capable of measuring neurological problems quantitatively are becoming readily available. Examples include the use of oculometers to measure eye movements and accelerometers to measure tremor. Many applications are being developed for use on smartphones. The benefits include not just more accurate disease quantification, but also consistency of data for longitudinal studies, accurate stratification of patients for entry into trials, and the possibility of automated data capture for remote follow-up. In this mini review, we will look at movement disorders with a particular focus on Parkinson's disease, describe some of the limitations of existing clinical evaluation tools, and illustrate the ways in which objective metrics have already been successful.

A Comparison of Change Blindness in Real-World and On-Screen Viewing of Museum Artefacts

Change blindness is a phenomenon of visual perception that occurs when a stimulus undergoes a change without this being noticed by its observer. To date, the effect has been produced by changing images displayed on screen as well as changing people and objects in an individual's environment. In this experiment, we combine these two approaches to directly compare the levels of change blindness produced in real-world vs. on-screen viewing of museum artefacts. In the real-world viewing condition, one group of participants viewed a series of pairs of similar but slightly different artefacts across eye saccades, while in the on-screen viewing condition, a second group of participants viewed the same artefacts across camera pans on video captured from a head-mounted camera worn by the first set of participants. We present three main findings. First, that change blindness does occur in a museum setting when similar ancient artefacts are viewed briefly one after another in both real-world and on-screen viewing conditions. We discuss this finding in relation to the notion that visual perceptual performance may be enhanced within museums. Second, we found that there was no statistically significant difference between the mean levels of change blindness produced in real-world and on-screen viewing conditions (real-world 42.62%, on-screen 47.35%, X² = 1.626, p > 0.05 1 d.f.). We discuss possible implications of these results for understanding change blindness, such as the role of binocular vs. monocular vision and that of head and eye movements, as well as reflecting on the evolution of change detection systems, and the impact of the experimental design itself on our results. Third, we combined the data from both viewing conditions to identify groups of artefacts that were independently associated with high and low levels of change blindness, and show that change detection rates were influenced mainly by bottom-up factors, including the visible area and contrast of changes. Finally, we discuss the limitations of this experiment and look to future directions for research into museum perception, change blindness, real-world and on-screen comparisons, and the role of bottom-up and top-down factors in the perception of change.

Acute impairment of saccadic eye movements is associated with delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage

OBJECTIVE

Delayed cerebral ischemia (DCI) causing cerebral infarction remains a significant cause of morbidity and mortality following aneurysmal subarachnoid hemorrhage (aSAH). Early brain injury in the first 72 hours following rupture is likely to play a key role in the pathophysiology underlying DCI but remains difficult to quantify objectively. Current diagnostic modalities are based on the concept of vasoconstriction causing cerebral ischemia and infarction and are either invasive or have a steep learning curve and user variability. The authors sought to determine whether saccadic eye movements are impaired following aSAH and whether this measurement in the acute period is associated with the likelihood of developing DCI.

METHODS

As part of a prospective, observational cohort study, 24 male and female patients (mean age 53 years old, range 31–70 years old) were recruited. Inclusion criteria included presentation with World Federation of Neurosurgical Societies (WFNS) Grades 1 or 2 (“good grade”) aSAH on admission and endovascular treatment within 72 hours of aneurysmal rupture. DCI and DCI-related cerebral infarction were defined according to consensus guidelines. Saccadometry data were collected at 3 time points in patients: in the first 72 hours, between Days 5 and 10, and at 3 months after aSAH. Data from 10 healthy controls was collected on 1 occasion for comparison.

RESULTS

Age-adjusted saccadic latency in patients was significantly prolonged in the first 72 hours following aSAH when compared with controls (188.7 msec [95% CI 176.9–202.2 msec] vs 160.7 msec [95% CI 145.6–179.4 msec], respectively; p = 0.0054, t-test). By 3 months after aSAH, there was no significant difference in median saccadic latency compared with controls (188.7 msec [95% CI 176.9–202.2 msec] vs 180.0 msec [95% CI 165.1–197.8 msec], respectively; p = 0.4175, t-test). Patients diagnosed with cerebral infarction due to DCI had a significantly higher age-adjusted saccadic latency in the first 72 hours than those without infarction (240.6 msec [95% CI 216.7–270.3 msec] vs 204.1 msec [95% CI 190.7–219.5 msec], respectively; p = 0.0157, t-test). This difference was more pronounced during Days 5–10 following aSAH, the peak incidence for DCI (303.7 msec [95% CI 266.7–352.7 msec] vs 207.6 msec [95% CI 193.7–223.6 msec], respectively; p < 0.0001, t-test). A binary generalized linear model showed that latency in the first 72 hours was the only significant predictor of cerebral infarction (p = 0.0185).

CONCLUSIONS

This is the first study to use saccadometry to measure the saccadic latency of eye movements in patients with aSAH during the acute period following aneurysm rupture. The results showed that median saccadic latency is associated with the risk of developing cerebral infarction due to DCI and may act as a potential objective biomarker to guide the need for intensive care admission and treatment. Future studies will look to formally validate saccadic latency as a biomarker of DCI in a larger cohort and assess whether the addition of saccades improves current clinical models for predicting patients at risk.

Using Saccadometry with Deep Brain Stimulation to Study Normal and Pathological Brain Function

The oculomotor system involves a large number of brain areas including parts of the basal ganglia, and various neurodegenerative diseases including Parkinson's and Huntington's can disrupt it. People with Parkinson's disease, for example, tend to have increased saccadic latencies. Consequently, the quantitative measurement of saccadic eye movements has received considerable attention as a potential biomarker for neurodegenerative conditions. A lot more can be learned about the brain in both health and disease by observing what happens to eye movements when the function of specific brain areas is perturbed. Deep brain stimulation is a surgical intervention used for the management of a range of neurological conditions including Parkinson's disease, in which stimulating electrodes are placed in specific brain areas including several sites in the basal ganglia. Eye movement measurements can then be made with the stimulator systems both off and on and the results compared. With suitable experimental design, this approach can be used to study the pathophysiology of the disease being treated, the mechanism by which DBS exerts it beneficial effects, and even aspects of normal neurophysiology.

The effect of acetazolamide on saccadic latency at 3459 meters

OBJECTIVE

The effect of altitude on brain function is not yet well understood, nor is the influence of height and speed of ascent. Additionally, the relationship between acute mountain sickness (AMS) symptoms and brain function at altitude is unclear. We hypothesized that a deterioration from baseline measures of brain function occurs after rapid, mechanical ascent to 3459 m and would be less pronounced in persons taking acetazolamide.

METHODS

In this double blind, randomized, placebo-controlled study, 20 healthy volunteers (14 men, 6 women; mean age [±SD] 43 ± 16 years) were alternately allocated to acetazolamide 250 mg or to placebo, taken every 12 hours commencing 3 days before ascent. Prosaccadic and antisaccadic eye movements, heart rate, arterial saturation, and Lake Louise AMS scores were assessed at sea level and 15 to 22 hours after ascent to 3459 m.

RESULTS

Arterial oxygen saturation was significantly lower in the placebo group compared to the acetazolamide group at altitude (Wilcoxon signed-rank test, median [interquartile range]: acetazolamide vs placebo: 92% [5] vs 85% [5]; P = .007), with no differences in prosaccadic latency, heart rate, or Lake Louise score. No differences in saccadic latencies from baseline to altitude were observed in the placebo group, whereas prosaccadic latencies were significantly longer at altitude with acetazolamide (altitude vs baseline: 153 ms [41] vs 176 ms [52], P = .008).

CONCLUSIONS

Brain function, measured by saccadic eye movements, appears to be unimpaired after rapid ascent to 3459 m. Although acetazolamide improves oxygen saturations, it may worsen prosaccades, possibly indicating adverse effects of acetazolamide on brain function at moderate altitude.

Learning and Recognition of a Non-conscious Sequence of Events in Human Primary Visual Cortex

Human primary visual cortex (V1) has long been associated with learning simple low-level visual discriminations [1] and is classically considered outside of neural systems that support high-level cognitive behavior in contexts that differ from the original conditions of learning, such as recognition memory [2, 3]. Here, we used a novel fMRI-based dichoptic masking protocol—designed to induce activity in V1, without modulation from visual awareness—to test whether human V1 is implicated in human observers rapidly learning and then later (15–20 min) recognizing a non-conscious and complex (second-order) visuospatial sequence. Learning was associated with a change in V1 activity, as part of a temporo-occipital and basal ganglia network, which is at variance with the cortico-cerebellar network identified in prior studies of “implicit” sequence learning that involved motor responses and visible stimuli (e.g., [4]). Recognition memory was associated with V1 activity, as part of a temporo-occipital network involving the hippocampus, under conditions that were not imputable to mechanisms associated with conscious retrieval. Notably, the V1 responses during learning and recognition separately predicted non-conscious recognition memory, and functional coupling between V1 and the hippocampus was enhanced for old retrieval cues. The results provide a basis for novel hypotheses about the signals that can drive recognition memory, because these data (1) identify human V1 with a memory network that can code complex associative serial visuospatial information and support later non-conscious recognition memory-guided behavior (cf. [5]) and (2) align with mouse models of experience-dependent V1 plasticity in learning and memory [6].

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Sequence learning and recognition memory can operate without visual awareness

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V1, hippocampus, and basal ganglia support learning of a non-conscious sequence

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Old/new status of non-conscious recognition probes modulates V1-hippocampal coupling

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V1 activity predicts non-conscious recognition memory performance

A Computational Cognitive Biomarker for Early-Stage Huntington's Disease

Huntington's disease (HD) is genetically determined but with variability in symptom onset, leading to uncertainty as to when pharmacological intervention should be initiated. Here we take a computational approach based on neurocognitive phenotyping, computational modeling, and classification, in an effort to provide quantitative predictors of HD before symptom onset. A large sample of subjects-consisting of both pre-manifest individuals carrying the HD mutation (pre-HD), and early symptomatic-as well as healthy controls performed the antisaccade conflict task, which requires executive control and response inhibition. While symptomatic HD subjects differed substantially from controls in behavioral measures [reaction time (RT) and error rates], there was no such clear behavioral differences in pre-HD. RT distributions and error rates were fit with an accumulator-based model which summarizes the computational processes involved and which are related to identified mechanisms in more detailed neural models of prefrontal cortex and basal ganglia. Classification based on fitted model parameters revealed a key parameter related to executive control differentiated pre-HD from controls, whereas the response inhibition parameter declined only after symptom onset. These findings demonstrate the utility of computational approaches for classification and prediction of brain disorders, and provide clues as to the underlying neural mechanisms.

Eye movements discriminate fatigue due to chronotypical factors and time spent on task--a double dissociation

Systematic differences in circadian rhythmicity are thought to be a substantial factor determining inter-individual differences in fatigue and cognitive performance. The synchronicity effect (when time of testing coincides with the respective circadian peak period) seems to play an important role. Eye movements have been shown to be a reliable indicator of fatigue due to sleep deprivation or time spent on cognitive tasks. However, eye movements have not been used so far to investigate the circadian synchronicity effect and the resulting differences in fatigue. The aim of the present study was to assess how different oculomotor parameters in a free visual exploration task are influenced by: a) fatigue due to chronotypical factors (being a 'morning type' or an 'evening type'); b) fatigue due to the time spent on task. Eighteen healthy participants performed a free visual exploration task of naturalistic pictures while their eye movements were recorded. The task was performed twice, once at their optimal and once at their non-optimal time of the day. Moreover, participants rated their subjective fatigue. The non-optimal time of the day triggered a significant and stable increase in the mean visual fixation duration during the free visual exploration task for both chronotypes. The increase in the mean visual fixation duration correlated with the difference in subjectively perceived fatigue at optimal and non-optimal times of the day. Conversely, the mean saccadic speed significantly and progressively decreased throughout the duration of the task, but was not influenced by the optimal or non-optimal time of the day for both chronotypes. The results suggest that different oculomotor parameters are discriminative for fatigue due to different sources. A decrease in saccadic speed seems to reflect fatigue due to time spent on task, whereas an increase in mean fixation duration a lack of synchronicity between chronotype and time of the day.

Principal component analysis of the cytokine and chemokine response to human traumatic brain injury

There is a growing realisation that neuro-inflammation plays a fundamental role in the pathology of Traumatic Brain Injury (TBI). This has led to the search for biomarkers that reflect these underlying inflammatory processes using techniques such as cerebral microdialysis. The interpretation of such biomarker data has been limited by the statistical methods used. When analysing data of this sort the multiple putative interactions between mediators need to be considered as well as the timing of production and high degree of statistical co-variance in levels of these mediators. Here we present a cytokine and chemokine dataset from human brain following human traumatic brain injury and use principal component analysis and partial least squares discriminant analysis to demonstrate the pattern of production following TBI, distinct phases of the humoral inflammatory response and the differing patterns of response in brain and in peripheral blood. This technique has the added advantage of making no assumptions about the Relative Recovery (RR) of microdialysis derived parameters. Taken together these techniques can be used in complex microdialysis datasets to summarise the data succinctly and generate hypotheses for future study.

Deep brain stimulation: eye movements reveal anomalous effects of electrode placement and stimulation

One of the major difficulties in evaluating the efficacy of deep brain stimulation (DBS), or understanding its mechanism, is the need to distinguish the effects of stimulation itself from those of the lesion inevitably created during surgery. Recent work has shown that DBS of the subthalamic nucleus in Parkinson's disease greatly reduces the time it takes the eyes to make a saccade in response to a visual stimulus. Since this saccadic latency can be rapidly and objectively measured, we used it to compare the effects of surgery and of stimulation. We used a saccadometer to measure the saccadic latencies of 9 DBS patients (1) preoperatively, (2) the day after insertion of subthalamic nucleus electrodes, (3) three weeks later, prior to turning on the stimulator, and (4) after commencement of stimulation. Patients were on their anti-Parkinsonian medication throughout the study. It revealed an entirely unexpected and puzzling finding. As in previous studies an amelioration of symptoms is seen immediately after surgery, and then a further improvement when finally the stimulator is turned on, but in the case of saccadic latency the pattern is different: surgery produces a transient increase in latency, returning to baseline within three weeks, while subsequent stimulation reduced latency. Thus the differential effects of electrode placement and stimulation are completely different for saccades and for more general motor symptoms. This important finding rules out some over-simple interpretations of the mechanism of DBS, and needs to be taken into account in future attempts at modelling the neurophysiology of DBS.

The search for biomarkers in Parkinson's disease: a critical review

Parkinson's disease (PD) is a progressive neurodegenerative disorder that primarily presents with features of bradykinesia, rigidity and tremor, and has, as part of its core pathology, the degeneration of dopaminergic neurons in the substantia nigra pars compacta. There is a great need for the development of a reliable diagnostic tool to improve promptness of diagnosis, definition of disease subtypes, and to monitor disease progression and demonstrate treatment efficacy in the case of disease modifying therapies. Current biomarkers range from objective clinical tools, to neuroimaging, to 'wet' markers involving blood and cerebrospinal fluid. To date, all candidate biomarkers for PD have failed to be developed into a clinically useful tool. Ideally, a combination of sensitive markers will be needed, not only to predict the onset of PD, but also to help in subtype classification and to follow progression. Here, we critically review various PD biomarker studies.

Diagnostic potential of saccadometry in progressive supranuclear palsy

Background: Progressive supranuclear palsy (PSP), an atypical parkinsonian syndrome characterized by extrapyramidal features, imbalance, supranuclear gaze paresis and dementia, can be difficult to diagnose, especially in the early stages. From the clinician’s point of view, the main difficulty with this disorder is the inability to provide an accurate diagnosis, at least for the initial stages of the disease, where symptoms are often confused with other parkinsonian disorders. This inability complicates the recruitment of patients with early-stage parkinsonism to trials of disease-modifying therapy. Objectives: To determine whether quantitative, objective examination of saccadic latency distributions can help to distinguish PSP patients from other groups of parkinsonian patients. Materials & methods: We used a newly developed portable saccadometer to compare saccadic latency distributions of a group of PSP patients with two other groups in whom the initial differential diagnosis included PSP: one of these groups had Parkinson’s disease and the other had developed a range of parkinsonian conditions (multiple system atrophy, dementia with Lewy bodies and corticobasal degeneration). Results: The use of a combination of saccadic parameters provided a greater discriminative power than the use of only one parameter, such as median latency. Statistical analysis and parameterization of the distributions robustly distinguished the three groups. Conclusions: This approach appears to have considerable diagnostic potential in allowing a more accurate diagnosis of PSP, and may help particularly to eliminate misdiagnosis with other parkinsonian conditions.

Saccadometry: a new tool for evaluating presymptomatic Huntington patients

Saccadic reaction time or latency reflects the operation of the largely cortical mechanisms that decide where to look. An unusual feature of latency is that it varies randomly from trial to trial. In the past, this variation has been regarded as a nuisance, but analysis of its statistical properties has turned out to provide much insight into the underlying cerebral decision mechanisms. Thanks to recent technological improvements, large number of data can be gathered quickly and noninvasively using miniature, portable devices, offering the possibility of using saccadometry as a biomarker to enhance the diagnosis and monitoring of neurological conditions. Here we show that this technique can robustly distinguish genetically identified presymptomatic and symptomatic Huntington's disease patients from age-matched controls, largely through an increase in the number of unusually early responses, which might reflect an impairment of the tonic suppression of the colliculus normally mediated by pathways through the basal ganglia.