Vigilance, alertness, or sustained attention: physiological basis and measurement

Lapsing during sleep deprivation is associated with distributed changes in brain activation

Lapses of attention manifest as delayed behavioral responses to salient stimuli. Although they can occur even after a normal night's sleep, they are longer in duration and more frequent after sleep deprivation (SD). To identify changes in task-associated brain activation associated with lapses during SD, we performed functional magnetic resonance imaging during a visual, selective attention task and analyzed the correct responses in a trial-by-trial manner modeling the effects of response time. Separately, we compared the fastest 10% and slowest 10% of correct responses in each state. Both analyses concurred in finding that SD-related lapses differ from lapses of equivalent duration after a normal night's sleep by (1) reduced ability of frontal and parietal control regions to raise activation in response to lapses, (2) dramatically reduced visual sensory cortex activation, and (3) reduced thalamic activation during lapses that contrasted with elevated thalamic activation during nonlapse periods. Despite these differences, the fastest responses after normal sleep and after SD elicited comparable frontoparietal activation, suggesting that performing a task while sleep deprived involves periods of apparently normal neural activation interleaved with periods of depressed cognitive control, visual perceptual functions, and arousal. These findings reveal for the first time some of the neural consequences of the interaction between efforts to maintain wakefulness and processes that initiate involuntary sleep in sleep-deprived persons.

EEG-vigilance differences between patients with borderline personality disorder, patients with obsessive-compulsive disorder and healthy controls

The regulation of brain activation, as assessed with the EEG, is a state modulated trait. A decline to lowered EEG-vigilance states has been found to be associated with emotional instability in older studies, but has not been systematically studied in patients with borderline personality disorder (BPD). Twenty unmedicated BPD patients were compared to 20 unmedicated patients with obsessive-compulsive disorder (OCD) as well as 20 healthy controls concerning their EEG-vigilance regulation over a 5-min period assessed with an algorithm classifying every artefact-free 2-s EEG segment into the EEG-vigilance state (A1-A3, B (=non-A)). If the alpha power was posterior more than 55% of the whole alpha power (anterior + posterior) in the artefact-free EEG-segments, that segment was marked as A1, if it was anterior more than 55% of the whole alpha power, as A3. For A2 the following rule was defined: Posterior or anterior alpha between 50 and 55% of the whole alpha power.BPD patients showed significantly lower rates of EEG-vigilance state A compared to OCD patients, indicating a lowered EEG-vigilance. All three groups showed a decrease in the rate of EEG-vigilance state A over the 5 min recording period in line with a lowering of vigilance. The study provides evidence for a less stable regulation of EEG-vigilance in BPD compared to OCD patients and is in line with concepts postulating that the behavioural pattern with sensation seeking and impulsivity in BPD has a compensatory and autoregulatory function to stabilize activation of the CNS.

Estimating vigilance in driving simulation using probabilistic PCA

In avoiding fatal consequences in accidents behind steering wheel caused by low level vigilance, EEG has shown bright prospects. In this paper, we propose a novel method for discriminating two different vigilance states of the subjects, namely wake state and sleep state, during driving a car in a simulation environment. After filtering the EEG data into a specific frequency band, we use probabilistic principle component analysis (PPCA) to reduce the data dimension. Then we model each vigilance state as a lower dimension Gaussian random variable by applying PPCA again. The feature related to class posterior probability is calculated for classification. The experimental results show satisfying time resolution (< or = 5s) and high accuracy (> or = 96%) across five subjects on both common frequency bands beta (19-26 Hz) and gamma (38-42 Hz), and a broad band (8-30 Hz).

Dynamic clustering for vigilance analysis based on EEG

Electroencephalogram (EEG) is the most commonly studied signal for vigilance estimation. Up to now, many researches mainly focus on using supervised learning methods for analyzing EEG data. However, it is hard to obtain enough labeled EEG data to cover the whole vigilance states, and sometimes the labeled EEG data may be not reliable in practice. In this paper, we propose a dynamic clustering method based on EEG to estimate vigilance states. This method uses temporal series information to supervise EEG data clustering. Experimental results show that our method can correctly discriminate between the wakefulness and the sleepiness for every 2 seconds through EEG, and can also distinguish two other middle states between wakefulness and sleepiness.

The amplitude and phase precision of 40 Hz auditory steady-state response depend on the level of arousal

The aim of this study was to investigate, in healthy subjects, the modulation of amplitude and phase precision of the auditory steady-state response (ASSR) to 40 Hz stimulation in two resting conditions varying in the level of arousal. Previously, ASSR measures have shown to be affected by the level of arousal, but the findings are somewhat controversial. Generally, ASSR is diminished in sleep but it may be increased in drowsiness. Besides, ASSR reduction has been observed in schizophrenia. However, schizophrenic patients are known to have a disturbance of arousal level, what makes it pertinent to know the effects of fluctuations in arousal on passive response to gamma-range stimulation. In nine healthy volunteers trains of 40 Hz click stimuli were applied during two conditions: in the "high arousal" condition subjects were sitting upright silently reading a book of interest; in the "low arousal" condition subjects were sitting in a reclined position with eyes closed and the lights turned off. The 64-channel EEG data was wavelet transformed and the amplitude and phase precision of the wavelet transformed evoked potential were decomposed by the recently proposed multi-subject non-negative multi-way factorization (NMWF) (Morup et al. in J Neurosci Methods 161:361-368, 2007). The estimates of these measures were subjected to statistical analysis. The amplitude and phase precision of the ASSR were significantly larger during the low arousal state compared to the high arousal condition. The modulation of ASSR amplitude and phase precision by differences in the arousal level during recording warrants caution when investigating oscillatory brain activity and interpreting the findings of reduced ASSR in schizophrenia. It also emphasizes the necessity of standardized recording procedures and monitoring the level of arousal during ASSR testing.

Topiramate effects on the EEG and alertness in healthy volunteers: a different profile of antiepileptic drug neurotoxicity

OBJECTIVE

Previous quantitative EEG (QEEG) studies of carbamazepine (CBZ), oxcarbazepine (OXC), and phenytoin (PHT) revealed a pattern of EEG slowing and an increase in drowsiness on the awake maintenance task (AMT). EEG slowing has been shown to correlate with negative effects on cognitive tests. Topiramate (TPM) is a novel AED with relatively large negative effects on cognitive function. We tested the hypothesis that TPM would induce significant slowing of EEG background rhythms and an increase in AMT drowsiness.

METHODS

Forty healthy volunteers were randomized to TPM, gabapentin (GBP), or placebo. Doses were escalated as tolerated to a maximum of 400mg/day for TPM or 3600 mg/day for GBP, over a 10-week period, followed by a minimum 2-week plateau period. Volunteers underwent an EEG, cognitive tests, and the AMT prior to starting an AED and again 12 weeks later. The EEG was captured using a structured recording protocol and quantified using the fast Fourier transform. Four target measures were derived from the averaged occipital electrodes (peak frequency of the dominant posterior rhythm, median frequency, percentage theta, and percentage delta). Test-retest changes for all measures were scored against similar test-retest distributions previously obtained from untreated healthy volunteers.

RESULTS

TPM produced no significant change in any of the four target EEG measures or on the AMT, even though several target cognitive tests revealed moderate or greater negative effects. There were also no significant changes in the placebo group. GBP slowed the peak and median frequency EEG measures and increased the percentage of theta and delta activity. Neither TPM, GBP, nor placebo caused a significant increase in drowsiness on the AMT.

CONCLUSIONS

TPM has a unique neurotoxicity profile. It has no effect on EEG background measures or on the AMT, but induces moderate to large negative changes in many cognitive test scores. This profile differs from those of CBZ, OXC, PHT, and GBP.

Visual attention, reaction time, and self-reported alertness upon awakening from sleep bouts of varying lengths

The aim of the present study was to examine visual attention, especially the executive control functions that deal with conflict, when participants were in a low arousal state shortly after a nighttime awakening. Fifteen participants spent four consecutive nights at a laboratory and performed a flankers task using two levels of target-distractor spacing (0.75 degrees and 1.50 degrees) and three trial types (compatible, incompatible, and neutral). The first night was a habituation night. For the next three nights, participants went to sleep at 2300 hours and were then awakened at either 2400 hours (1-h sleep bout), 0300 hours (4-h sleep bout), or 0600 hours (7-h sleep bout) and were administered a flankers task and a self-report questionnaire that measured arousal level. These testing times were counter-balanced across participants, and a 2100 hours (pre-sleep) flankers task was also randomly assigned to be completed on one of the testing nights. Response time on neutral-flanker trials was increased if participants were awakened from a sleep bout and was slowest at 0300 hours, appearing to parallel circadian body temperature. In contrast, failures of selective attention, as indexed by the difference between compatible and incompatible trials, increased linearly as a function of the length of the sleep bout. Compared to the 2100 hours pre-sleep condition, self-reported energy was lower and Tiredness was higher after awakening from a sleep bout. Taken together, the current data suggest a dissociation between the processes that perform a non-conflict task and the executive control of attention. Specifically, longer sleep bouts seem to be associated with greater difficulty in inhibiting task-irrelevant information, perhaps due to a sleep inertia effect affecting the anterior cingulate cortex.