Errors in nonword repetition: bridging short- and long-term memory

According to the working memory model, the phonological loop is the component of working memory specialized in processing and manipulating limited amounts of speech-based information. The Children's Test of Nonword Repetition (CNRep) is a suitable measure of phonological short-term memory for English-speaking children, which was validated by the Brazilian Children's Test of Pseudoword Repetition (BCPR) as a Portuguese-language version. The objectives of the present study were: i) to investigate developmental aspects of the phonological memory processing by error analysis in the nonword repetition task, and ii) to examine phoneme (substitution, omission and addition) and order (migration) errors made in the BCPR by 180 normal Brazilian children of both sexes aged 4-10, from preschool to 4th grade. The dominant error was substitution [F(3,525) = 180.47; P < 0.0001]. The performance was age-related [F(4,175) = 14.53; P < 0.0001]. The length effect, i.e., more errors in long than in short items, was observed [F(3,519) = 108.36; P < 0.0001]. In 5-syllable pseudowords, errors occurred mainly in the middle of the stimuli, before the syllabic stress [F(4,16) = 6.03; P = 0.003]; substitutions appeared more at the end of the stimuli, after the stress [F(12,48) = 2.27; P = 0.02]. In conclusion, the BCPR error analysis supports the idea that phonological loop capacity is relatively constant during development, although school learning increases the efficiency of this system. Moreover, there are indications that long-term memory contributes to holding memory trace. The findings were discussed in terms of distinctiveness, clustering and redintegration hypotheses.

Sleep disorders, sleepiness and traffic safety: a public health menace

Sleep disorders are not uncommon and have been widely reported throughout the world. They have a profound impact on industrialized 24-h societies. Consequences of these problems include impaired social and recreational activities, increased human errors, loss of productivity, and elevated risk of accidents. Conditions such as acute and chronic insomnia, sleep loss, excessive sleepiness, shift-work, jet lag, narcolepsy, and sleep apnea warrant public health attention, since residual sleepiness during the day may affect performance of daily activities such as driving a car. Benzodiazepine hypnotics and zopiclone promote sleep, both having residual effects the following day including sleepiness and reduced alertness. In contrast, the non-benzodiazepine hypnotics zolpidem and zaleplon have no significant next-day residual effects when taken as recommended. Research on the effects of wakefulness-promoting drugs on driving ability is limited. Countermeasures for excessive daytime sleepiness have a limited effect. There is a need for a social awareness program to educate the public about the potential consequences of various sleep disorders such as narcolepsy, sleep apnea, shift-work-related sleep loss, and excessive daytime sleepiness in order to reduce the number of sleep-related traffic accidents.

Use of magnitude-squared coherence to identify the maximum driving response band of the somatosensory evoked potential

The present study proposes to apply magnitude-squared coherence (MSC) to the somatosensory evoked potential for identifying the maximum driving response band. EEG signals, leads [Fpz'-Cz'] and [C3'-C4'], were collected from two groups of normal volunteers, stimulated at the rate of 4.91 (G1: 26 volunteers) and 5.13 Hz (G2: 18 volunteers). About 1400 stimuli were applied to the right tibial nerve at the motor threshold level. After applying the anti-aliasing filter, the signals were digitized and then further low-pass filtered (200 Hz, 6th order Butterworth and zero-phase). Based on the rejection of the null hypothesis of response absence (MSC(f) > 0.0060 with 500 epochs and the level of significance set at a = 0.05), the beta and gamma bands, 15-66 Hz, were identified as the maximum driving response band. Taking both leads together ("logical-OR detector", with a false-alarm rate of a = 0.05, and hence a = 0.0253 for each derivation), the detection exceeded 70% for all multiples of the stimulation frequency within this range. Similar performance was achieved for MSC of both leads but at 15, 25, 35, and 40 Hz. Moreover, the response was detected in [C3'-C4'] at 35.9 Hz and in [Fpz'-Cz'] at 46.2 Hz for all members of G2. Using the "logical-OR detector" procedure, the response was detected at the 7th multiple of the stimulation frequency for the series as a whole (considering both groups). Based on these findings, the MSC technique may be used for monitoring purposes.

Relationship between Brazilian airline pilot errors and time of day

Flight safety is one of the most important and frequently discussed issues in aviation. Recent accident inquiries have raised questions as to how the work of flight crews is organized and the extent to which these conditions may have been contributing factors to accidents. Fatigue is based on physiologic limitations, which are reflected in performance deficits. The purpose of the present study was to provide an analysis of the periods of the day in which pilots working for a commercial airline presented major errors. Errors made by 515 captains and 472 copilots were analyzed using data from flight operation quality assurance systems. To analyze the times of day (shifts) during which incidents occurred, we divided the light-dark cycle (24:00) in four periods: morning, afternoon, night, and early morning. The differences of risk during the day were reported as the ratio of morning to afternoon, morning to night and morning to early morning error rates. For the purposes of this research, level 3 events alone were taken into account, since these were the most serious in which company operational limits were exceeded or when established procedures were not followed. According to airline flight schedules, 35% of flights take place in the morning period, 32% in the afternoon, 26% at night, and 7% in the early morning. Data showed that the risk of errors increased by almost 50% in the early morning relative to the morning period (ratio of 1:1.46). For the period of the afternoon, the ratio was 1:1.04 and for the night a ratio of 1:1.05 was found. These results showed that the period of the early morning represented a greater risk of attention problems and fatigue.

Hot cognition and activation of the medial prefrontal cortex: Self-regulating in contexts involving motivational pressures

The medial prefrontal cortex (mPFC) is involved in performance-monitoring and has been implicated in the generation of several electrocortical responses associated with self-regulation. The error-related negativity (ERN), the inhibitory Nogo N2 (N2), and the feedback-related negativity (FRN) are event-related potential (ERP) components which reflect mPFC activity associated with feedback to behavioural (ERN, N2) and environmental (FRN) consequences. Our main goal was to determine whether or not rnPFC activation varies as a function of motivational context (e.g., those involving performance-related incentives) or the use of internally versus externally generated feedback signals (i.e., errors). Additionally, we assessed medial prefrontal activity in relation to individual differences in personality and temperament. Participants completed a combination of tasks in which performance-related incentives were associated with task performance and feedback generated from internal versus external responses. MPFC activity was indexed using both ERP scalp voltage peaks and intracerebral current source density (CSD) of dorsal and ventral regions. Additionally, participants completed several questionnaires assessing personality and temperament styles. Given previous studies have shown that enhanced mPFC activity to loss (or negative) feedback, we expected that activity in the mPFC would generally be greater during the Loss condition relative to the Win condition for both the ERN and N2. Also, due to the evidence that the (vmPFC) is engaged in arousing contexts, we hypothesized that activity in the ventromedial prefrontal cortex (vmPFC) would be greater than activity in the dorsomedial prefrontal cortex (dmPFC), especially in the Loss condition of the GoNogo task (ERN). Similarly, loss feedback in the BART (FRN) was expected to engage the vmPFC more than the dmPFC. Finally, we predicted that persons rating themselves as more willing to engage in approach-related behaviours or to exhibit rigid cognitive styles would show reduced activity of the mPFC. Overall, our results emphasize the role of affective evaluations of behavioural and environmental consequences when self-regulating. Although there were no effects of context on brain activity, our data indicate that, during the time of the ERN and N2 on the MW Go-Nogo task and the FRN on the BART, the vrnPFC was more active compared to the dmPFC. Moreover, regional recruitment in the mPFC was similar across internally (ERN) and externally (FRN) generated errors signals associated with loss feedback, as reflected by relatively greater activity in the vmPFC than the dmPFC. Our data also suggest that greater activity in the mPFC is associated with better inhibitory control, as reflected by both scalp and CSD measures. Additionally, deactivation of the subgenual anterior cingulate cortex (sgACC) and lower levels of self-reported positive affect were both related to increased voluntary risk-taking on the BART. Finally, persons reporting higher levels of approach-related behaviour or cognitive rigidity showed reduced activity of the mPFC. These results are in line with previous research emphasizing that affect/motivation is central to the processes reflected by mediofrontal negativities (MFNs), that the vmPFC is involved in regulating demands on motivational/affective systems, and that the underlying mechanisms driving these functions vary across both individuals and contexts.

Frontal Lobe Function and Performance Monitoring following Total Sleep Deprivation

Imaging studies have shown reduced frontal lobe resources following total sleep deprivation (TSD). The anterior cingulate cortex (ACC) in the frontal region plays a role in performance monitoring and cognitive control; both error detection and response inhibition are impaired following sleep loss. Event-related potentials (ERPs) are an electrophysiological tool used to index the brain's response to stimuli and information processing. In the Flanker task, the error-related negativity (ERN) and error positivity (Pe) ERPs are elicited after erroneous button presses. In a Go/NoGo task, NoGo-N2 and NoGo-P3 ERPs are elicited during high conflict stimulus processing. Research investigating the impact of sleep loss on ERPs during performance monitoring is equivocal, possibly due to task differences, sample size differences and varying degrees of sleep loss. Based on the effects of sleep loss on frontal function and prior research, it was expected that the sleep deprivation group would have lower accuracy, slower reaction time and impaired remediation on performance monitoring tasks, along with attenuated and delayed stimulus- and response-locked ERPs. In the current study, 49 young adults (24 male) were screened to be healthy good sleepers and then randomly assigned to a sleep deprived (n = 24) or rested control (n = 25) group. Participants slept in the laboratory on a baseline night, followed by a second night of sleep or wake. Flanker and Go/NoGo tasks were administered in a battery at 1O:30am (i.e., 27 hours awake for the sleep deprivation group) to measure performance monitoring. On the Flanker task, the sleep deprivation group was significantly slower than controls (p's <.05), but groups did not differ on accuracy. No group differences were observed in post-error slowing, but a trend was observed for less remedial accuracy in the sleep deprived group compared to controls (p = .09), suggesting impairment in the ability to take remedial action following TSD. Delayed P300s were observed in the sleep deprived group on congruent and incongruent Flanker trials combined (p = .001). On the Go/NoGo task, the hit rate (i.e., Go accuracy) was significantly lower in the sleep deprived group compared to controls (p <.001), but no differences were found on false alarm rates (i.e., NoGo Accuracy). For the sleep deprived group, the Go-P3 was significantly smaller (p = .045) and there was a trend for a smaller NoGo-N2 compared to controls (p = .08). The ERN amplitude was reduced in the TSD group compared to controls in both the Flanker and Go/NoGo tasks. Error rate was significantly correlated with the amplitude of response-locked ERNs in control (r = -.55, p=.005) and sleep deprived groups (r = -.46, p = .021); error rate was also correlated with Pe amplitude in controls (r = .46, p=.022) and a trend was found in the sleep deprived participants (r = .39, p =. 052). An exploratory analysis showed significantly larger Pe mean amplitudes (p = .025) in the sleep deprived group compared to controls for participants who made more than 40+ errors on the Flanker task. Altered stimulus processing as indexed by delayed P3 latency during the Flanker task and smaller amplitude Go-P3s during the Go/NoGo task indicate impairment in stimulus evaluation and / or context updating during frontal lobe tasks. ERN and NoGoN2 reductions in the sleep deprived group confirm impairments in the monitoring system. These data add to a body of evidence showing that the frontal brain region is particularly vulnerable to sleep loss. Understanding the neural basis of these deficits in performance monitoring abilities is particularly important for our increasingly sleep deprived society and for safety and productivity in situations like driving and sustained operations.

Photograph Negatives - Donald Ziraldo driving Tractor

Two photograph negatives of Donald Ziraldo driving a tractor through vineyards.

Receipt from Jas. Murphy, St. Catharines for driving

Receipt from Jas. Murphy, St. Catharines for driving, April 13, 1887.

The FCLT with Dependent Errors: an Helicopter Tour of the Quality of the Approximation

This note investigates the adequacy of the finite-sample approximation provided by the Functional Central Limit Theorem (FCLT) when the errors are allowed to be dependent. We compare the distribution of the scaled partial sums of some data with the distribution of the Wiener process to which it converges. Our setup is purposely very simple in that it considers data generated from an ARMA(1,1) process. Yet, this is sufficient to bring out interesting conclusions about the particular elements which cause the approximations to be inadequate in even quite large sample sizes.

Testing Mean-Variance Efficiency in CAPM with Possibly Non-Gaussian Errors : An Exact Simulation-Based Approach

In this paper we propose exact likelihood-based mean-variance efficiency tests of the market portfolio in the context of Capital Asset Pricing Model (CAPM), allowing for a wide class of error distributions which include normality as a special case. These tests are developed in the frame-work of multivariate linear regressions (MLR). It is well known however that despite their simple statistical structure, standard asymptotically justified MLR-based tests are unreliable. In financial econometrics, exact tests have been proposed for a few specific hypotheses [Jobson and Korkie (Journal of Financial Economics, 1982), MacKinlay (Journal of Financial Economics, 1987), Gib-bons, Ross and Shanken (Econometrica, 1989), Zhou (Journal of Finance 1993)], most of which depend on normality. For the gaussian model, our tests correspond to Gibbons, Ross and Shanken’s mean-variance efficiency tests. In non-gaussian contexts, we reconsider mean-variance efficiency tests allowing for multivariate Student-t and gaussian mixture errors. Our framework allows to cast more evidence on whether the normality assumption is too restrictive when testing the CAPM. We also propose exact multivariate diagnostic checks (including tests for multivariate GARCH and mul-tivariate generalization of the well known variance ratio tests) and goodness of fit tests as well as a set estimate for the intervening nuisance parameters. Our results [over five-year subperiods] show the following: (i) multivariate normality is rejected in most subperiods, (ii) residual checks reveal no significant departures from the multivariate i.i.d. assumption, and (iii) mean-variance efficiency tests of the market portfolio is not rejected as frequently once it is allowed for the possibility of non-normal errors.

Correcting the Errors : A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities

This note develops general model-free adjustment procedures for the calculation of unbiased volatility loss functions based on practically feasible realized volatility benchmarks. The procedures, which exploit the recent asymptotic distributional results in Barndorff-Nielsen and Shephard (2002a), are both easy to implement and highly accurate in empirically realistic situations. On properly accounting for the measurement errors in the volatility forecast evaluations reported in Andersen, Bollerslev, Diebold and Labys (2003), the adjustments result in markedly higher estimates for the true degree of return-volatility predictability.