Carrie R. H. Innes

Sensory-motor and cognitive tests predict driving ability of persons with brain disorders

OBJECTIVE Brain disorders can lead to a decreased ability to perform the physical and cognitive functions necessary for safe driving. This study aimed to determine how accurately a battery of computerized sensory-motor and cognitive tests (SMCTests) could predict driving abilities in persons with brain disorders. METHODS SMCTests and an independent on-road driving assessment were applied to 50 experienced drivers with brain disorders referred to a hospital-based driving assessment service. The patients comprised 36 males and 14 females, a mean age of 71.3 years (range 43-85 years) and diagnoses of 35 stroke, 4 traumatic brain injury, 4 Alzheimers disease, and 7 other. Binary logistic regression (BLR) and nonlinear causal resource analysis (NCRA) were used to build model equations for prediction of on-road driving ability based on SMCTests performance. RESULTS BLR and NCRA correctly classified 94% and 90% of referrals respectively as on-road pass or fail. Leave-one-out cross-validation estimated that BLR and NCRA would correctly predict the classification of 86% and 76% respectively of an independent referral group as on-road pass or fail. CONCLUSIONS Compared with other studies, SMCTests have shown the highest predictive accuracy against true on-road driving ability as estimated in an independent data set and in persons with brain disorders. SMCTests also have the advantage of being able to comprehensively and objectively assess both sensory-motor and higher cognitive functions related to driving.

Losing the struggle to stay awake: Divergent thalamic and cortical activity during microsleeps

Maintaining alertness is critical for safe and successful performance of most human activities. Consequently, microsleeps during continuous visuomotor tasks, such as driving, can be very serious, not only disrupting performance but sometimes leading to injury or death due to accidents. We have investigated the neural activity underlying behavioral microsleeps – brief (0.5–15 s) episodes of complete failure to respond accompanied by slow eye‐closures – and EEG theta activity during drowsiness in a continuous task. Twenty healthy normally‐rested participants performed a 50‐min continuous tracking task while fMRI, EEG, eye‐video, and responses were simultaneously recorded. Visual rating of performance and eye‐video revealed that 70% of the participants had frequent microsleeps. fMRI analysis revealed a transient decrease in thalamic, posterior cingulate, and occipital cortex activity and an increase in frontal, posterior parietal, and parahippocampal activity during microsleeps. The transient activity was modulated by the duration of the microsleep. In subjects with frequent microsleeps, power in the post‐central EEG theta was positively correlated with the BOLD signal in the thalamus, basal forebrain, and visual, posterior parietal, and prefrontal cortices. These results provide evidence for distinct neural changes associated with microsleeps and with EEG theta activity during drowsiness in a continuous task. They also suggest that the occurrence of microsleeps during an active task is not a global deactivation process but involves localized activation of fronto‐parietal cortex, which, despite a transient loss of arousal, may constitute a mechanism by which these regions try to restore responsiveness. Hum Brain Mapp 35:257–269, 2014.

Cerebral Perfusion Differences Between Drowsy and Nondrowsy Individuals After Acute Sleep Restriction

OBJECTIVES To investigate changes in resting cerebral blood flow (CBF) after acute sleep restriction. To investigate the extent to which changes in CBF after sleep restriction are related to drowsiness as manifested in eye-video. DESIGN Participants were scanned for 5 min using arterial spin labeling (ASL) perfusion imaging after both sleep-restricted and rested nights. Participants were rated for visual signs of drowsiness in the eye-video recorded during the scan. SETTING Lying supine in a 3-Tesla magnetic resonance imaging scanner. PARTICIPANTS Twenty healthy adults (age 20-37 yr) with no history of neurologic, psychiatric, or sleep disorder, and with usual time in bed of 7.0-8.5 h. INTERVENTIONS In the night before the sleep-restricted session, participants were restricted to 4 h time in bed. RESULTS There was an overall reduction in CBF in the right-lateralized fronto-parietal attentional network after acute sleep restriction, although this was largely driven by participants who showed strong signs of drowsiness in the eye-video after sleep restriction. Change in CBF correlated with change in drowsiness in the basal forebrain-cingulate regions. In particular, there was a pronounced increase in CBF in the basal forebrain and anterior and posterior cingulate cortex of participants who remained alert after sleep restriction. CONCLUSIONS The pattern of cerebral activity after acute sleep restriction is highly dependent on level of drowsiness. Nondrowsy individuals are able to increase activity in the arousal-promoting brain regions and maintain activity in attentional regions. In contrast, drowsy individuals are unable to maintain arousal and show decreased activity in both arousal-promoting and attentional regions.

Performance in normal subjects on a novel battery of driving-related sensory-motor and cognitive tests

Currently, there is no international standard for the assessment of fitness to drive for cognitively or physically impaired persons. A computerized battery of driving-related sensory-motor and cognitive tests (SMCTests) has been developed, comprising tests of visuoperception, visuomotor ability, complex attention, visual search, decision making, impulse control, planning, and divided attention. Construct validity analysis was conducted in 60 normal, healthy subjects and showed that, overall, the novel cognitive tests assessed cognitive functions similar to a set of standard neuropsychological tests. The novel tests were found to have greater perceived face validity for predicting on-road driving ability than was found in the equivalent standard tests. Test—retest stability and reliability of SMCTests measures, as well as correlations between SMCTests and on-road driving, were determined in a subset of 12 subjects. The majority of test measures were stable and reliable across two sessions, and significant correlations were found between on-road driving scores and measures from ballistic movement, footbrake reaction, hand-control reaction, and complex attention. The substantial face validity, construct validity, stability, and reliability of SMCTests, together with the battery’s level of correlation with on-road driving in normal subjects, strengthen our confidence in the ability of SMCTests to detect and identify sensory-motor and cognitive deficits related to unsafe driving and increased risk of accidents.

Comparison of a linear and a non-linear model for using sensory-motor, cognitive, personality, and demographic data to predict driving ability in healthy older adults

This study compared the ability of binary logistic regression (BLR) and non-linear causal resource analysis (NCRA) to utilize a range of cognitive, sensory-motor, personality and demographic measures to predict driving ability in a sample of cognitively healthy older drivers. Participants were sixty drivers aged 70 and above (mean=76.7 years, 50% men) with no diagnosed neurological disorder. Test data was used to build classification models for a Pass or Fail score on an on-road driving assessment. The generalizability of the models was estimated using leave-one-out cross-validation. Sixteen participants (27%) received an on-road Fail score. Area under the ROC curve values were .76 for BLR and .88 for NCRA (no significant difference, z=1.488, p=.137). The ROC curve was used to select three different cut-points for each model and to compare classification. At the cut-point corresponding to the maximum average of sensitivity and specificity, the BLR model had a sensitivity of 68.8% and specificity of 75.0% while NCRA had a sensitivity of 75.0% and specificity of 95.5%. However, leave-one-out cross-validation reduced sensitivity in both models and particularly reduced specificity for NCRA. Neither model is accurate enough to be relied on solely for determination of driving ability. The lowered accuracy of the models following leave-one-out cross-validation highlights the importance of investigating models beyond classification alone in order to determine a models ability to generalize to new cases.

Decreased Regional Cerebral Perfusion in Moderate-Severe Obstructive Sleep Apnoea during Wakefulness.

STUDY OBJECTIVES To investigate gray matter volume and concentration and cerebral perfusion in people with untreated obstructive sleep apnea (OSA) while awake. DESIGN Voxel-based morphometry to quantify gray matter concentration and volume. Arterial spin labeling perfusion imaging to quantify cerebral perfusion. SETTING Lying supine in a 3-T magnetic resonance imaging scanner in the early afternoon. PARTICIPANTS 19 people with OSA (6 females, 13 males; mean age 56.7 y, range 41-70; mean AHI 18.5, range 5.2-52.8) and 19 controls (13 females, 6 males; mean age: 50.0 y, range 41-81). INTERVENTIONS N/A. MEASUREMENTS AND RESULTS There were no differences in regional gray matter concentration or volume between participants with OSA and controls. Neither was there any difference in regional perfusion between controls and people with mild OSA (n = 11). However, compared to controls, participants with moderate-severe OSA (n = 8) had decreased perfusion (while awake) in three clusters. The largest cluster incorporated, bilaterally, the paracingulate gyrus, anterior cingulate gyrus, and subcallosal cortex, and the left putamen and left frontal orbital cortex. The second cluster was right-lateralized, incorporating the posterior temporal fusiform cortex, parahippocampal gyrus, and hippocampus. The third cluster was located in the right thalamus. CONCLUSIONS There is decreased regional perfusion during wakefulness in participants with moderate-severe obstructive sleep apnea, and these are in brain regions which have shown decreased regional gray matter volume in previous studies in people with severe OSA. Thus, we hypothesize that cerebral perfusion changes are evident before (and possibly underlie) future structural changes.

Source-space ICA for EEG source separation, localization, and time-course reconstruction.

We propose source-space independent component analysis (ICA) for separation, tomography, and time-course reconstruction of EEG and MEG source signals. Source-space ICA is based on the application of singular value decomposition and ICA on the neuroelectrical signals from all brain voxels obtained post minimum-variance beamforming of sensor-space EEG or MEG. We describe the theoretical background and equations, then evaluate the performance of this technique in several different situations, including weak sources, bilateral correlated sources, multiple sources, and cluster sources. In this approach, tomographic maps of sources are obtained by back-projection of the ICA mixing coefficients into the source-space (3-D brain template). The advantages of source-space ICA over the popular alternative approaches of sensor-space ICA together with dipole fitting and power mapping via minimum-variance beamforming are demonstrated. Simulated EEG data were produced by forward head modeling to project the simulated sources onto scalp sensors, then superimposed on real EEG background. To illustrate the application of source-space ICA to real EEG source reconstruction, we show the localization and time-course reconstruction of visual evoked potentials. Source-space ICA is superior to the minimum-variance beamforming in the reconstruction of multiple weak and strong sources, as ICA allows weak sources to be identified and reconstructed in the presence of stronger sources. Source-space ICA is also superior to sensor-space ICA on accuracy of localization of sources, as source-space ICA applies ICA to the time-courses of voxels reconstructed from minimum-variance beamforming on a 3D scanning grid and these time-courses are optimally unmixed via the beamformer. Each component identified by source-space ICA has its own tomographic map which shows the extent to which each voxel has contributed to that component.

fMRI correlates of behavioural microsleeps during a continuous visuomotor task

Behavioural microsleeps (BMs) are brief episodes of absent responsiveness accompanied by slow-eye-closure. They frequently occur as a consequence of sleep-deprivation, an extended monotonous task, and are modulated by the circadian rhythm and sleep homeostatic pressure. In this paper, a multimodal method to investigate the neural correlates of BMs using simultaneous recording of fMRI, eye-video, VEOG, and continuous visuomotor response is presented. The data were collected from 20 healthy volunteers while they performed a continuous visuomotor tracking task inside an MRI scanner for 50 min. The BMs were identified post-hoc by expert visual rating of eye-video and visuomotor response using a set of pre-defined criteria. fMRI analysis of BMs revealed changes in haemodynamic activity in several cortical and sub-cortical regions associated with visuomotor control and arousal.

Lapses of responsiveness: Characteristics, detection, and underlying mechanisms

Lapses in responsiveness (‘lapses’), particularly microsleeps and attention lapses, are complete disruptions in performance from ∼0.5–15 s. They are of particular importance in the transport sector in which there is a need to maintain sustained attention for extended periods and in which lapses can lead to multiple-fatality accidents.

Distinct neural correlates of time-on-task and transient errors during a visuomotor tracking task after sleep restriction

Sleep loss leads to both time-on-task slowing of responsiveness and increased frequency of transient response errors. The consequences of such errors during real-world visuomotor tasks, such as driving, are serious and life threatening. To investigate the neuronal underpinning of time-on-task and transient errors during a visuomotor tracking task following sleep restriction, we performed fMRI on 20 healthy individuals when well-rested and when sleep-restricted while they performed a 2-D pursuit-tracking task. Sleep restriction to 4-h time-in-bed was associated with significant time-on-task decline in tracking performance and an increased number of transient tracking errors. Sleep restriction was associated with time-on-task decreases in BOLD activity in task-related areas, including the lateral occipital cortex, intraparietal cortex, and primary motor cortex. In contrast, thalamic, anterior cingulate, and medial frontal cortex areas showed overall increases irrespective of time-on-task after sleep-restriction. Furthermore, transient errors after sleep-restriction were associated with distinct transient BOLD activations in areas not involved in tracking task per se, in the right superior parietal cortex, bilateral temporal cortex, and thalamus. These results highlight the distinct cerebral underpinnings of sustained and transient modulations in alertness during increased homeostatic drive to sleep. Ability to detect neuronal changes associated with both sustained and transient changes in performance in a single task allowed us to disentangle neuronal mechanisms underlying two important aspects of sustained task performance following sleep loss.